Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Finnish
Size:
10K<n<100K
License:
Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
- README.md +1 -0
- turku_ner_corpus.py +39 -38
README.md
CHANGED
@@ -1,4 +1,5 @@
|
|
1 |
---
|
|
|
2 |
annotations_creators:
|
3 |
- expert-generated
|
4 |
language_creators:
|
|
|
1 |
---
|
2 |
+
pretty_name: Turku NER corpus
|
3 |
annotations_creators:
|
4 |
- expert-generated
|
5 |
language_creators:
|
turku_ner_corpus.py
CHANGED
@@ -14,7 +14,6 @@
|
|
14 |
# limitations under the License.
|
15 |
|
16 |
# Lint as: python3
|
17 |
-
import os
|
18 |
|
19 |
import datasets
|
20 |
|
@@ -73,47 +72,63 @@ class TurkuNERCorpus(datasets.GeneratorBasedBuilder):
|
|
73 |
)
|
74 |
|
75 |
def _split_generators(self, dl_manager):
|
76 |
-
|
77 |
return [
|
78 |
datasets.SplitGenerator(
|
79 |
name=datasets.Split.TRAIN,
|
80 |
-
gen_kwargs={"
|
81 |
),
|
82 |
datasets.SplitGenerator(
|
83 |
name=datasets.Split.VALIDATION,
|
84 |
-
gen_kwargs={"
|
85 |
),
|
86 |
datasets.SplitGenerator(
|
87 |
name=datasets.Split.TEST,
|
88 |
-
gen_kwargs={"
|
89 |
),
|
90 |
]
|
91 |
|
92 |
-
def _generate_examples(self,
|
93 |
if data_type == "train":
|
94 |
-
data_path =
|
95 |
elif data_type == "valid":
|
96 |
-
data_path =
|
97 |
elif data_type == "test":
|
98 |
-
data_path =
|
99 |
else:
|
100 |
raise Exception("data_type not understood")
|
101 |
|
102 |
sentence_counter = 0
|
103 |
-
|
104 |
-
|
105 |
-
|
106 |
-
|
107 |
-
row
|
108 |
-
|
109 |
-
|
110 |
-
|
111 |
-
|
112 |
-
|
113 |
-
|
114 |
-
|
115 |
-
|
116 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
117 |
sentence = (
|
118 |
sentence_counter,
|
119 |
{
|
@@ -122,19 +137,5 @@ class TurkuNERCorpus(datasets.GeneratorBasedBuilder):
|
|
122 |
"ner_tags": current_labels,
|
123 |
},
|
124 |
)
|
125 |
-
sentence_counter += 1
|
126 |
-
current_words = []
|
127 |
-
current_labels = []
|
128 |
yield sentence
|
129 |
-
|
130 |
-
# if something remains:
|
131 |
-
if current_words:
|
132 |
-
sentence = (
|
133 |
-
sentence_counter,
|
134 |
-
{
|
135 |
-
"id": str(sentence_counter),
|
136 |
-
"tokens": current_words,
|
137 |
-
"ner_tags": current_labels,
|
138 |
-
},
|
139 |
-
)
|
140 |
-
yield sentence
|
|
|
14 |
# limitations under the License.
|
15 |
|
16 |
# Lint as: python3
|
|
|
17 |
|
18 |
import datasets
|
19 |
|
|
|
72 |
)
|
73 |
|
74 |
def _split_generators(self, dl_manager):
|
75 |
+
archive = dl_manager.download(_URL)
|
76 |
return [
|
77 |
datasets.SplitGenerator(
|
78 |
name=datasets.Split.TRAIN,
|
79 |
+
gen_kwargs={"files": dl_manager.iter_archive(archive), "data_type": "train"},
|
80 |
),
|
81 |
datasets.SplitGenerator(
|
82 |
name=datasets.Split.VALIDATION,
|
83 |
+
gen_kwargs={"files": dl_manager.iter_archive(archive), "data_type": "valid"},
|
84 |
),
|
85 |
datasets.SplitGenerator(
|
86 |
name=datasets.Split.TEST,
|
87 |
+
gen_kwargs={"files": dl_manager.iter_archive(archive), "data_type": "test"},
|
88 |
),
|
89 |
]
|
90 |
|
91 |
+
def _generate_examples(self, files, data_type):
|
92 |
if data_type == "train":
|
93 |
+
data_path = "turku-ner-corpus-1.0/data/conll/train.tsv"
|
94 |
elif data_type == "valid":
|
95 |
+
data_path = "turku-ner-corpus-1.0/data/conll/dev.tsv"
|
96 |
elif data_type == "test":
|
97 |
+
data_path = "turku-ner-corpus-1.0/data/conll/test.tsv"
|
98 |
else:
|
99 |
raise Exception("data_type not understood")
|
100 |
|
101 |
sentence_counter = 0
|
102 |
+
for path, f in files:
|
103 |
+
if path == data_path:
|
104 |
+
current_words = []
|
105 |
+
current_labels = []
|
106 |
+
for row in f:
|
107 |
+
row = row.decode("utf-8").rstrip()
|
108 |
+
row_split = row.split("\t")
|
109 |
+
if len(row_split) == 2:
|
110 |
+
token, label = row_split
|
111 |
+
current_words.append(token)
|
112 |
+
current_labels.append(label)
|
113 |
+
else:
|
114 |
+
if not current_words:
|
115 |
+
continue
|
116 |
+
assert len(current_words) == len(current_labels), "word len doesnt match label length"
|
117 |
+
sentence = (
|
118 |
+
sentence_counter,
|
119 |
+
{
|
120 |
+
"id": str(sentence_counter),
|
121 |
+
"tokens": current_words,
|
122 |
+
"ner_tags": current_labels,
|
123 |
+
},
|
124 |
+
)
|
125 |
+
sentence_counter += 1
|
126 |
+
current_words = []
|
127 |
+
current_labels = []
|
128 |
+
yield sentence
|
129 |
+
|
130 |
+
# if something remains:
|
131 |
+
if current_words:
|
132 |
sentence = (
|
133 |
sentence_counter,
|
134 |
{
|
|
|
137 |
"ner_tags": current_labels,
|
138 |
},
|
139 |
)
|
|
|
|
|
|
|
140 |
yield sentence
|
141 |
+
break
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|