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en_pipeline

Token Classification
spaCy
English
Eval Results
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ShivamRai7 commited on
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updated_model

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Files changed (16) hide show
  1. .gitattributes +2 -0
  2. README.md +56 -0
  3. config.cfg +144 -0
  4. en_pipeline-any-py3-none-any.whl +3 -0
  5. meta.json +132 -0
  6. ner/cfg +13 -0
  7. ner/model +0 -0
  8. ner/moves +1 -0
  9. tok2vec/cfg +3 -0
  10. tok2vec/model +3 -0
  11. tokenizer +3 -0
  12. vocab/key2row +1 -0
  13. vocab/lookups.bin +3 -0
  14. vocab/strings.json +2231 -0
  15. vocab/vectors +0 -0
  16. vocab/vectors.cfg +3 -0
.gitattributes CHANGED
@@ -32,3 +32,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ en_pipeline-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,56 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - spacy
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+ - token-classification
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+ language:
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+ - en
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+ model-index:
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+ - name: en_pipeline
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+ results:
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+ - task:
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+ name: NER
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+ type: token-classification
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+ metrics:
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+ - name: NER Precision
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+ type: precision
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+ value: 0.9907407407
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+ - name: NER Recall
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+ type: recall
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+ value: 0.9960106383
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.9933687003
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+ ---
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_pipeline` |
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+ | **Version** | `0.0.0` |
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+ | **spaCy** | `>=3.5.1,<3.6.0` |
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+ | **Default Pipeline** | `tok2vec`, `ner` |
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+ | **Components** | `tok2vec`, `ner` |
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+ | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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+ | **Sources** | n/a |
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+ | **License** | n/a |
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+ | **Author** | [n/a]() |
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+
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+ ### Label Scheme
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+
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+ <details>
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+
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+ <summary>View label scheme (14 labels for 1 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`ner`** | `BOOK`, `COMODITY`, `CONTAINER COUNT`, `CONTAINER SIZE`, `CONTAINER SIZE-COUNT`, `DESTINATION`, `ENQUIRY`, `HELP`, `INCOTERM`, `KYC`, `ORIGIN`, `SEARCH RATES`, `SHIP`, `SHIPMENT TYPE` |
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+
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+ </details>
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+
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+ ### Accuracy
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+
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+ | Type | Score |
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+ | --- | --- |
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+ | `ENTS_F` | 99.34 |
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+ | `ENTS_P` | 99.07 |
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+ | `ENTS_R` | 99.60 |
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+ | `TOK2VEC_LOSS` | 6119.15 |
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+ | `NER_LOSS` | 67099.47 |
config.cfg ADDED
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+ [paths]
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+ train = "spacy_model/training_data.spacy"
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+ dev = "spacy_model/training_data.spacy"
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+ vectors = null
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+ init_tok2vec = null
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+
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+ [system]
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+ gpu_allocator = null
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+ seed = 0
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+
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+ [nlp]
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+ lang = "en"
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+ pipeline = ["tok2vec","ner"]
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+ batch_size = 1000
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+ disabled = []
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+ before_creation = null
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+ after_creation = null
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+ after_pipeline_creation = null
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+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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+
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+ [components]
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+
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+ [components.ner]
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+ factory = "ner"
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+ incorrect_spans_key = null
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+ moves = null
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+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.ner.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ state_type = "ner"
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+ extra_state_tokens = false
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+ hidden_width = 64
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+ maxout_pieces = 2
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+ use_upper = true
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
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+ width = ${components.tok2vec.model.encode.width}
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+ upstream = "*"
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+
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+ [components.tok2vec]
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+ factory = "tok2vec"
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+
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+ [components.tok2vec.model]
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+ @architectures = "spacy.Tok2Vec.v2"
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+
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+ [components.tok2vec.model.embed]
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+ @architectures = "spacy.MultiHashEmbed.v2"
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+ width = ${components.tok2vec.model.encode.width}
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+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
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+ rows = [5000,1000,2500,2500]
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+ include_static_vectors = false
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+
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+ [components.tok2vec.model.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
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+ width = 96
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+ depth = 4
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+ window_size = 1
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+ maxout_pieces = 3
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+
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+ [corpora]
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+
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+ [corpora.dev]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.dev}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [corpora.train]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [training]
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+ dev_corpus = "corpora.dev"
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+ train_corpus = "corpora.train"
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+ seed = ${system.seed}
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+ gpu_allocator = ${system.gpu_allocator}
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+ dropout = 0.1
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+ accumulate_gradient = 1
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+ patience = 1600
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+ max_epochs = 0
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+ max_steps = 20000
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+ eval_frequency = 200
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+ frozen_components = []
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+ annotating_components = []
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+ before_to_disk = null
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+ before_update = null
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+
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+ [training.batcher]
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+ @batchers = "spacy.batch_by_words.v1"
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+ discard_oversize = false
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+ tolerance = 0.2
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+ get_length = null
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+
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+ [training.batcher.size]
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+ @schedules = "compounding.v1"
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+ start = 100
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+ stop = 1000
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+ compound = 1.001
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+ t = 0.0
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+
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+ [training.logger]
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+ @loggers = "spacy.ConsoleLogger.v1"
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+ progress_bar = false
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+
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+ [training.optimizer]
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+ @optimizers = "Adam.v1"
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+ beta1 = 0.9
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+ beta2 = 0.999
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+ L2_is_weight_decay = true
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+ L2 = 0.01
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+ grad_clip = 1.0
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+ use_averages = false
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+ eps = 0.00000001
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+ learn_rate = 0.001
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+
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+ [training.score_weights]
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+ ents_f = 1.0
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+ ents_p = 0.0
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+ ents_r = 0.0
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+ ents_per_type = null
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+
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+ [pretraining]
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+
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+ [initialize]
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+ vectors = ${paths.vectors}
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+ init_tok2vec = ${paths.init_tok2vec}
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+ vocab_data = null
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+ lookups = null
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+ before_init = null
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+ after_init = null
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+
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+ [initialize.components]
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+
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+ [initialize.tokenizer]
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ner/cfg ADDED
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ner/model ADDED
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tok2vec/cfg ADDED
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tokenizer ADDED
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+ "Singapore",
856
+ "Sokhna",
857
+ "Somethin",
858
+ "Somethin'",
859
+ "Somethin\u2019",
860
+ "South",
861
+ "South Carolina",
862
+ "Spain",
863
+ "Special",
864
+ "Specialized",
865
+ "Sri",
866
+ "St",
867
+ "St.",
868
+ "Supply",
869
+ "Sydney",
870
+ "T",
871
+ "TES",
872
+ "TKD",
873
+ "TMB",
874
+ "TO",
875
+ "TZDAR",
876
+ "Taiwan",
877
+ "Tanzania",
878
+ "Temperature",
879
+ "Tenn",
880
+ "Tenn.",
881
+ "Tennessee",
882
+ "That",
883
+ "That's",
884
+ "That\u2019s",
885
+ "There",
886
+ "There's",
887
+ "There\u2019s",
888
+ "These",
889
+ "They",
890
+ "This",
891
+ "This's",
892
+ "This\u2019s",
893
+ "Those",
894
+ "Tihi",
895
+ "To",
896
+ "Tokyo",
897
+ "Town",
898
+ "Track",
899
+ "Trade",
900
+ "Tuticorin",
901
+ "Tuticorine",
902
+ "Two",
903
+ "Type",
904
+ "Tyre",
905
+ "U",
906
+ "UAE",
907
+ "UNG",
908
+ "UNT",
909
+ "USA",
910
+ "USNYC",
911
+ "Ummqasr",
912
+ "Urgent",
913
+ "V",
914
+ "V.V",
915
+ "V_V",
916
+ "Va",
917
+ "Va.",
918
+ "Vancouver",
919
+ "Virginia",
920
+ "Vizag",
921
+ "Volume",
922
+ "W",
923
+ "WT",
924
+ "Warehouse",
925
+ "Warehousing",
926
+ "Was",
927
+ "Wash",
928
+ "Wash.",
929
+ "Washington",
930
+ "We",
931
+ "Were",
932
+ "What",
933
+ "What's",
934
+ "What\u2019s",
935
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936
+ "When's",
937
+ "When\u2019s",
938
+ "Where",
939
+ "Where's",
940
+ "Where\u2019s",
941
+ "Who",
942
+ "Who's",
943
+ "Who\u2019s",
944
+ "Why",
945
+ "Why's",
946
+ "Why\u2019s",
947
+ "Wis",
948
+ "Wis.",
949
+ "Wisconsin",
950
+ "Wo",
951
+ "Would",
952
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953
+ "X'xxxx",
954
+ "X++",
955
+ "X.",
956
+ "X.X",
957
+ "X.X.",
958
+ "X.x",
959
+ "X.x.",
960
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961
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962
+ "XDD",
963
+ "XX",
964
+ "XXX",
965
+ "XXXX",
966
+ "XXXX XXXX",
967
+ "XXXX XXXX-XXXX",
968
+ "XYZ",
969
+ "X_X",
970
+ "X_x",
971
+ "Xx",
972
+ "Xx'",
973
+ "Xx'x",
974
+ "Xx'xx",
975
+ "Xx.",
976
+ "Xx.X.",
977
+ "XxXX",
978
+ "Xxx",
979
+ "Xxx'x",
980
+ "Xxx.",
981
+ "Xxxx",
982
+ "Xxxx'",
983
+ "Xxxx'x",
984
+ "Xxxx.",
985
+ "Xxxxx",
986
+ "Xxxxx'",
987
+ "Xxxxx'x",
988
+ "Xxxxx-",
989
+ "Xxxxx.",
990
+ "Xxxxx\u2019",
991
+ "Xxxxx\u2019x",
992
+ "Xxxx\u2019",
993
+ "Xxxx\u2019x",
994
+ "Xxx\u2019x",
995
+ "Xx\u2019",
996
+ "Xx\u2019x",
997
+ "Xx\u2019xx",
998
+ "X\u2019x",
999
+ "X\u2019xxxx",
1000
+ "Y",
1001
+ "YPE",
1002
+ "Yemen",
1003
+ "York",
1004
+ "You",
1005
+ "Z",
1006
+ "ZINC",
1007
+ "Zealand",
1008
+ "Zurich",
1009
+ "[",
1010
+ "[-:",
1011
+ "[:",
1012
+ "[=",
1013
+ "\\",
1014
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1015
+ "\\n",
1016
+ "\\t",
1017
+ "\\x",
1018
+ "]",
1019
+ "]=",
1020
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1021
+ "^_^",
1022
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1023
+ "^___^",
1024
+ "_*)",
1025
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1026
+ "_.)",
1027
+ "_<)",
1028
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1029
+ "__-",
1030
+ "__^",
1031
+ "_\u00ac)",
1032
+ "_\u0ca0)",
1033
+ "a",
1034
+ "a.",
1035
+ "a.m",
1036
+ "a.m.",
1037
+ "abbas",
1038
+ "about",
1039
+ "accommodates",
1040
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1041
+ "ach",
1042
+ "ack",
1043
+ "ada",
1044
+ "ade",
1045
+ "aden",
1046
+ "adm",
1047
+ "adm.",
1048
+ "aejea",
1049
+ "africa",
1050
+ "age",
1051
+ "ago",
1052
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1053
+ "ain",
1054
+ "air",
1055
+ "aires",
1056
+ "ak",
1057
+ "ak.",
1058
+ "ala",
1059
+ "ala.",
1060
+ "ali",
1061
+ "all",
1062
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1063
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1064
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1065
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1066
+ "ami",
1067
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1068
+ "ana",
1069
+ "and",
1070
+ "and/or",
1071
+ "ang",
1072
+ "angeles",
1073
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1074
+ "ant",
1075
+ "any",
1076
+ "ape",
1077
+ "appropriate",
1078
+ "apr",
1079
+ "apr.",
1080
+ "ar.",
1081
+ "are",
1082
+ "ariz",
1083
+ "ariz.",
1084
+ "ark",
1085
+ "ark.",
1086
+ "arrange",
1087
+ "arranged",
1088
+ "arrangement",
1089
+ "arrangements",
1090
+ "arranging",
1091
+ "arries",
1092
+ "artwork",
1093
+ "artworks",
1094
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1095
+ "asa",
1096
+ "ase",
1097
+ "ash",
1098
+ "asr",
1099
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1100
+ "assist",
1101
+ "assistance",
1102
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1103
+ "at",
1104
+ "ate",
1105
+ "att",
1106
+ "aty",
1107
+ "auckland",
1108
+ "aug",
1109
+ "aug.",
1110
+ "australia",
1111
+ "automotive",
1112
+ "ava",
1113
+ "ave",
1114
+ "ays",
1115
+ "b",
1116
+ "b.",
1117
+ "bad",
1118
+ "bai",
1119
+ "ban",
1120
+ "bandar",
1121
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1122
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1123
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1124
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1125
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1126
+ "because",
1127
+ "beijing",
1128
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1129
+ "belongings",
1130
+ "berlin",
1131
+ "bhuj",
1132
+ "ble",
1133
+ "book",
1134
+ "booking",
1135
+ "border",
1136
+ "both",
1137
+ "bout",
1138
+ "br.",
1139
+ "brazil",
1140
+ "bros",
1141
+ "bros.",
1142
+ "buenos",
1143
+ "bul",
1144
+ "buneos",
1145
+ "busan",
1146
+ "buy",
1147
+ "c",
1148
+ "c'm",
1149
+ "c++",
1150
+ "c.",
1151
+ "ca",
1152
+ "cacar",
1153
+ "cal",
1154
+ "calif",
1155
+ "calif.",
1156
+ "callao",
1157
+ "can",
1158
+ "canada",
1159
+ "cape",
1160
+ "car",
1161
+ "care",
1162
+ "cargo",
1163
+ "cause",
1164
+ "cbm",
1165
+ "ce>",
1166
+ "ces",
1167
+ "cfr",
1168
+ "ch.",
1169
+ "chain",
1170
+ "channai",
1171
+ "charges",
1172
+ "chat",
1173
+ "chemical",
1174
+ "chennai",
1175
+ "chicago",
1176
+ "china",
1177
+ "chittagong",
1178
+ "cif",
1179
+ "clearance",
1180
+ "cmb",
1181
+ "cnsgh",
1182
+ "cnsnz",
1183
+ "co",
1184
+ "co.",
1185
+ "cold",
1186
+ "colo",
1187
+ "colo.",
1188
+ "colombo",
1189
+ "come",
1190
+ "commerce",
1191
+ "commodities",
1192
+ "commodities-",
1193
+ "comodity",
1194
+ "complete",
1195
+ "complex",
1196
+ "compliance",
1197
+ "confirm",
1198
+ "conn",
1199
+ "conn.",
1200
+ "consignment",
1201
+ "consolidated",
1202
+ "container",
1203
+ "container count",
1204
+ "container size",
1205
+ "container size-count",
1206
+ "containers",
1207
+ "controlled",
1208
+ "coordination",
1209
+ "corp",
1210
+ "corp.",
1211
+ "cos",
1212
+ "cost",
1213
+ "could",
1214
+ "courier",
1215
+ "coverage",
1216
+ "coz",
1217
+ "cross",
1218
+ "ct.",
1219
+ "cts",
1220
+ "customs",
1221
+ "cuz",
1222
+ "c\u2019m",
1223
+ "d",
1224
+ "d)",
1225
+ "d-",
1226
+ "d-)",
1227
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1228
+ "d.",
1229
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1230
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1231
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1232
+ "dX",
1233
+ "dXx",
1234
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1235
+ "d_x",
1236
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1237
+ "dam",
1238
+ "dar",
1239
+ "dare",
1240
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1241
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1242
+ "dd'X",
1243
+ "dd'XX",
1244
+ "dd'XXX",
1245
+ "dd'x",
1246
+ "dd'xx",
1247
+ "dd'xxx",
1248
+ "dd/dd",
1249
+ "dd/ddXx",
1250
+ "dd/ddxx",
1251
+ "ddXX",
1252
+ "ddXdd",
1253
+ "ddXx",
1254
+ "ddd",
1255
+ "dddd",
1256
+ "ddp",
1257
+ "ddx.x",
1258
+ "ddx.x.",
1259
+ "ddxX",
1260
+ "ddxdd",
1261
+ "ddxx",
1262
+ "de",
1263
+ "dec",
1264
+ "dec.",
1265
+ "ded",
1266
+ "del",
1267
+ "del.",
1268
+ "delhi",
1269
+ "delivery",
1270
+ "den",
1271
+ "der",
1272
+ "destination",
1273
+ "destinations",
1274
+ "details",
1275
+ "dia",
1276
+ "did",
1277
+ "distribution",
1278
+ "dle",
1279
+ "dm.",
1280
+ "do",
1281
+ "document",
1282
+ "documentation",
1283
+ "does",
1284
+ "doin",
1285
+ "doin'",
1286
+ "doing",
1287
+ "doin\u2019",
1288
+ "don",
1289
+ "dr",
1290
+ "dr.",
1291
+ "dra",
1292
+ "dri",
1293
+ "dry",
1294
+ "dubai",
1295
+ "durban",
1296
+ "dx",
1297
+ "dx.x",
1298
+ "dx.x.",
1299
+ "dxdd",
1300
+ "dxdd\u2019XX",
1301
+ "dxdd\u2019xx",
1302
+ "dxx",
1303
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1304
+ "e's",
1305
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1306
+ "e.g",
1307
+ "e.g.",
1308
+ "each",
1309
+ "eb.",
1310
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1311
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1312
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1313
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1314
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1315
+ "eet",
1316
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1317
+ "egypt",
1318
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1320
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1321
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1322
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1323
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1324
+ "en.",
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1327
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1328
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1329
+ "enquiry",
1330
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1331
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1332
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1334
+ "equipment",
1335
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1336
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1338
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1342
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1343
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1345
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+ "eva",
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1350
+ "express",
1351
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1352
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1353
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1354
+ "f.",
1355
+ "facilities",
1356
+ "fcl",
1357
+ "feb",
1358
+ "feb.",
1359
+ "feet",
1360
+ "felixstowe",
1361
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1362
+ "filled",
1363
+ "fla",
1364
+ "fla.",
1365
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1366
+ "for",
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+ "fragile",
1368
+ "frankfurt",
1369
+ "free",
1370
+ "freight",
1371
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1372
+ "from",
1373
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1376
+ "ftl",
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+ "full",
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+ "g",
1380
+ "g.",
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1382
+ "ga.",
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+ "gbo",
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+ "gdynia",
1385
+ "ged",
1386
+ "gen",
1387
+ "gen.",
1388
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+ "ght",
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+ "give",
1392
+ "glassware",
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+ "goin'",
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1396
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+ "gon",
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1401
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1402
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1457
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1460
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1461
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1467
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1470
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1471
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1472
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1475
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1476
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1477
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1478
+ "ind.",
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+ "indonesia",
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1484
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1485
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1498
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1500
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1513
+ "j.",
1514
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1515
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1516
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1517
+ "jan.",
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1521
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1522
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1525
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1529
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1531
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+ "kan.",
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1600
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1620
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1621
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1622
+ "messrs.",
1623
+ "miami",
1624
+ "mich",
1625
+ "mich.",
1626
+ "might",
1627
+ "milan",
1628
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1629
+ "minn",
1630
+ "minn.",
1631
+ "miss",
1632
+ "miss.",
1633
+ "mo",
1634
+ "mo.",
1635
+ "mogadishu",
1636
+ "mombasa",
1637
+ "mont",
1638
+ "mont.",
1639
+ "moradabad",
1640
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1641
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1642
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1643
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1644
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1645
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1646
+ "ms.",
1647
+ "mt",
1648
+ "mt.",
1649
+ "mudra",
1650
+ "mukalla",
1651
+ "multiple",
1652
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1653
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1654
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1655
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1656
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1657
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1658
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1659
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1660
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1661
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1662
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1663
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1664
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1665
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1666
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1667
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1668
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1669
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1670
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1671
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1672
+ "navsheva",
1673
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1674
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1675
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1676
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1677
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1678
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1679
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1680
+ "nebr.",
1681
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1682
+ "needed",
1683
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1684
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1685
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1686
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1687
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1688
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1689
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1690
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1691
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1692
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1693
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1694
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1695
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1696
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1697
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1698
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1699
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1700
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1701
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1702
+ "nothin'",
1703
+ "nothing",
1704
+ "nothin\u2019",
1705
+ "nouakchatt",
1706
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1707
+ "nov.",
1708
+ "novorossiysk",
1709
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1710
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1711
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1712
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1713
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1714
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1715
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1716
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1717
+ "nuthin",
1718
+ "nuthin'",
1719
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1720
+ "nya",
1721
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1722
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1723
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1724
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1725
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1726
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1727
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1728
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1729
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1730
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1731
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1732
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1733
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1734
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1735
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1736
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1737
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1738
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1739
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1740
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1741
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1742
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1743
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1744
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1745
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1746
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1747
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1748
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1749
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1750
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1751
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1752
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1753
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1754
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1755
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1756
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1757
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1758
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1759
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1760
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1761
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1762
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1763
+ "options",
1764
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1765
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1766
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1767
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1768
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1769
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1770
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1771
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1772
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1773
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1774
+ "ost",
1775
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1776
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1777
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1778
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1779
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1780
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1781
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1782
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1783
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1784
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1785
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1786
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1787
+ "o\u2019s",
1788
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1789
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1790
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1791
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1792
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1793
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1794
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1795
+ "pan",
1796
+ "paris",
1797
+ "parts",
1798
+ "ped",
1799
+ "per",
1800
+ "perishable",
1801
+ "permits",
1802
+ "personal",
1803
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1804
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1805
+ "pharmaceutical",
1806
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1807
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1808
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1809
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1810
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1811
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1812
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1813
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1814
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1815
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1816
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1817
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1818
+ "price",
1819
+ "proceed",
1820
+ "produce",
1821
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1822
+ "prof",
1823
+ "prof.",
1824
+ "project",
1825
+ "provide",
1826
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1827
+ "puerto",
1828
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1829
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1830
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1831
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1832
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1833
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1834
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1835
+ "rates",
1836
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1837
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1838
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1839
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1840
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1841
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1842
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1843
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1844
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1845
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1846
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1847
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1848
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1849
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1850
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1851
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1852
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1853
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1854
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1855
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1856
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1857
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1858
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1859
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1860
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1861
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1862
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1863
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1864
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1865
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1866
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1867
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1868
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1869
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1870
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1871
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1872
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1873
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1874
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1875
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1876
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1877
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1878
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1879
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1880
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1881
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1882
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1883
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1884
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1885
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1886
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1887
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1888
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1889
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1890
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1891
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1892
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1893
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1894
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1895
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1896
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1897
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1898
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1899
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1900
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1901
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1902
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1903
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1904
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1905
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1906
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1907
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1908
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1909
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1910
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1911
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1912
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1913
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1914
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1915
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1916
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1917
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1918
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1919
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1920
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1921
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1922
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1923
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1924
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1925
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1926
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1927
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1928
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1929
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1930
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1931
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1932
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1933
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1934
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1935
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1936
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1937
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1938
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1940
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1941
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1942
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1943
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1944
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1945
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1946
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1947
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1948
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1949
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1950
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1951
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1952
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1953
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1954
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1955
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1956
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1957
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1958
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1959
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1960
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1961
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1962
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1963
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1964
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1965
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1966
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1967
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1968
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1969
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1970
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1971
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1972
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1973
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1974
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1975
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1976
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1977
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1978
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1979
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1980
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1981
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1982
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1983
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1984
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1985
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1986
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1987
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1988
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1989
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1990
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1991
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1992
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1993
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1994
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1995
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1996
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1997
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1998
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1999
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2000
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2001
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2002
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2003
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2004
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2005
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2006
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2007
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2008
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2009
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2010
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2011
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2012
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2013
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2014
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2015
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2016
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2017
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2018
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2019
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2020
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2021
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2022
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2023
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2024
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2025
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2026
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2027
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2028
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2029
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2030
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2031
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2032
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2033
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2034
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2035
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2036
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2037
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2038
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2039
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2040
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2041
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2042
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2043
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2044
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2045
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2046
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2047
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2048
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2049
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2050
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2051
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2052
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2053
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2054
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2055
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2056
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2057
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2058
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2059
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2060
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2061
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2062
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2063
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2064
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2065
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2066
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2067
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2068
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2069
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2070
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2071
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2072
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2073
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2074
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2075
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2076
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2077
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2078
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2079
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2080
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2081
+ "why's",
2082
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2083
+ "will",
2084
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2085
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2086
+ "with",
2087
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2088
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2089
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2090
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2091
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2092
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2093
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2094
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2095
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2096
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2097
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2098
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2099
+ "x.x",
2100
+ "x.x.",
2101
+ "x/x",
2102
+ "x20",
2103
+ "x40",
2104
+ "xD",
2105
+ "xDD",
2106
+ "xX",
2107
+ "xXX",
2108
+ "x_X",
2109
+ "x_d",
2110
+ "x_x",
2111
+ "xd",
2112
+ "xdd",
2113
+ "xx",
2114
+ "xx'",
2115
+ "xx'x",
2116
+ "xx'xx",
2117
+ "xx.",
2118
+ "xxx",
2119
+ "xxx'x",
2120
+ "xxx/xx",
2121
+ "xxxx",
2122
+ "xxxx'",
2123
+ "xxxx'x",
2124
+ "xxxx-",
2125
+ "xxxx\u2019",
2126
+ "xxxx\u2019x",
2127
+ "xxx\u2019x",
2128
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2129
+ "xx\u2019x",
2130
+ "xx\u2019xx",
2131
+ "xyz",
2132
+ "x\u2019",
2133
+ "x\u2019x",
2134
+ "x\u2019xxxx",
2135
+ "x\ufe35x",
2136
+ "y",
2137
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2138
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2139
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2140
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2141
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2142
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2143
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2144
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2145
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2146
+ "ysk",
2147
+ "y\u2019",
2148
+ "y\u2019s",
2149
+ "z",
2150
+ "z.",
2151
+ "zag",
2152
+ "zealand",
2153
+ "zed",
2154
+ "zil",
2155
+ "zinc",
2156
+ "zurich",
2157
+ "|",
2158
+ "}",
2159
+ "\u00a0",
2160
+ "\u00ac",
2161
+ "\u00ac_\u00ac",
2162
+ "\u00af",
2163
+ "\u00af\\(x)/\u00af",
2164
+ "\u00af\\(\u30c4)/\u00af",
2165
+ "\u00b0",
2166
+ "\u00b0C.",
2167
+ "\u00b0F.",
2168
+ "\u00b0K.",
2169
+ "\u00b0X.",
2170
+ "\u00b0c.",
2171
+ "\u00b0f.",
2172
+ "\u00b0k.",
2173
+ "\u00b0x.",
2174
+ "\u00e4",
2175
+ "\u00e4.",
2176
+ "\u00f6",
2177
+ "\u00f6.",
2178
+ "\u00fc",
2179
+ "\u00fc.",
2180
+ "\u0ca0",
2181
+ "\u0ca0_\u0ca0",
2182
+ "\u0ca0\ufe35\u0ca0",
2183
+ "\u2013",
2184
+ "\u2014",
2185
+ "\u2018",
2186
+ "\u2018S",
2187
+ "\u2018X",
2188
+ "\u2018s",
2189
+ "\u2018x",
2190
+ "\u2019",
2191
+ "\u2019-(",
2192
+ "\u2019-)",
2193
+ "\u2019Cause",
2194
+ "\u2019Cos",
2195
+ "\u2019Coz",
2196
+ "\u2019Cuz",
2197
+ "\u2019HQ",
2198
+ "\u2019S",
2199
+ "\u2019X",
2200
+ "\u2019Xxx",
2201
+ "\u2019Xxxxx",
2202
+ "\u2019am",
2203
+ "\u2019bout",
2204
+ "\u2019cause",
2205
+ "\u2019cos",
2206
+ "\u2019coz",
2207
+ "\u2019cuz",
2208
+ "\u2019d",
2209
+ "\u2019em",
2210
+ "\u2019hq",
2211
+ "\u2019ll",
2212
+ "\u2019m",
2213
+ "\u2019nuff",
2214
+ "\u2019re",
2215
+ "\u2019s",
2216
+ "\u2019ve",
2217
+ "\u2019x",
2218
+ "\u2019xx",
2219
+ "\u2019xxx",
2220
+ "\u2019xxxx",
2221
+ "\u2019y",
2222
+ "\u2019\u2019",
2223
+ "\u201d",
2224
+ "\u2501",
2225
+ "\u253b",
2226
+ "\u253b\u2501\u253b",
2227
+ "\u256f",
2228
+ "\u25a1",
2229
+ "\ufe35",
2230
+ "\uff09"
2231
+ ]
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vocab/vectors.cfg ADDED
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