version: "0.8.0" corpusPath: "./resources/dataset/dataseer/corpus" templatePath: "./resources/dataset/dataseer/crfpp-templates/dataseer.template" grobidHome: "/opt/grobid/grobid-home" tmpPath: "/opt/grobid/grobid-home/tmp/" # path to Pub2TEI repository as available at https://github.com/kermitt2/Pub2TEI pub2teiPath: "/opt/Pub2TEI/" gluttonHost: gluttonPort: # entity-fishing server information for performing entity disambiguation # for https, indicate 443 as port entityFishingHost: cloud.science-miner.com/nerd entityFishingPort: 443 #entityFishingHost: localhost #entityFishingPort: 8090 # if true we use binary classifiers for the contexts, otherwise use a single multi-label classifier # binary classifiers perform better, but havier to use useBinaryContextClassifiers: false # sequence labeling model (identify data-related sections) models: # model for zones - name: "dataseer" engine: "wapiti" #engine: "delft" wapiti: # wapiti training parameters, they will be used at training time only epsilon: 0.00001 window: 20 nbMaxIterations: 2000 # classifier model, dataset binary (datset or not dataset in the current sentence) - name: "dataseer-binary" engine: "delft" delft: # deep learning parameters #architecture: "gru" architecture: "bert" #embeddings_name: "word2vec" transformer: "allenai/scibert_scivocab_cased" # identification of the data type (first level hierarchy) - name: "dataseer-first" engine: "delft" delft: # deep learning parameters #architecture: "gru" architecture: "bert" #embeddings_name: "word2vec" transformer: "allenai/scibert_scivocab_cased" # mention context classification (reuse binary for the moment) - name: "dataseer-reuse" engine: "delft" delft: # deep learning parameters #architecture: "gru" architecture: "bert" #embeddings_name: "word2vec" transformer: "allenai/scibert_scivocab_cased" # model for dataset mention recognition - name: "datasets" #engine: "wapiti" engine: "delft" wapiti: # wapiti training parameters, they will be used at training time only epsilon: 0.00001 window: 20 nbMaxIterations: 2000 delft: # deep learning parameters #architecture: "BidLSTM_CRF" architecture: "BERT_CRF" #transformer: "allenai/scibert_scivocab_cased" transformer: "michiyasunaga/LinkBERT-basecased" #useELMo: true #embeddings_name: "glove-840B" runtime: # parameters used at runtime/prediction max_sequence_length: 200 #max_sequence_length: 300 batch_size: 20 - name: "context" engine: "delft" delft: #architecture: "gru" #embeddings_name: "glove-840B" architecture: "bert" transformer: "michiyasunaga/LinkBERT-basecased" - name: "context_used" engine: "delft" delft: #architecture: "gru" #embeddings_name: "glove-840B" architecture: "bert" transformer: "michiyasunaga/LinkBERT-basecased" - name: "context_creation" engine: "delft" delft: #architecture: "gru" #embeddings_name: "glove-840B" architecture: "bert" transformer: "michiyasunaga/LinkBERT-basecased" - name: "context_shared" engine: "delft" delft: #architecture: "gru" #embeddings_name: "glove-840B" architecture: "bert" transformer: "michiyasunaga/LinkBERT-basecased" # Limit the maximum number of requests (0, no limit) maxParallelRequests: 0 # CORS configuration for the web API service corsAllowedOrigins: "*" corsAllowedMethods: "OPTIONS,GET,PUT,POST,DELETE,HEAD" corsAllowedHeaders: "X-Requested-With,Content-Type,Accept,Origin" server: type: custom idleTimeout: 120 seconds applicationConnectors: - type: http port: 8060 adminConnectors: - type: http port: 8061 registerDefaultExceptionMappers: false maxThreads: 2048 maxQueuedRequests: 2048 acceptQueueSize: 2048 requestLog: appenders: [] # these logging settings apply to the service usage mode logging: level: INFO loggers: org.apache.pdfbox.pdmodel.font.PDSimpleFont: "OFF" org.glassfish.jersey.internal: "OFF" com.squarespace.jersey2.guice.JerseyGuiceUtils: "OFF" appenders: - type: console threshold: INFO timeZone: UTC # uncomment to have the logs in json format #layout: # type: json