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ca3266f530
This includes two major features: 1. HTML view of CDA documents 2. simpletransformers-based NLP pipeline
55 lines
2.1 KiB
JSON
55 lines
2.1 KiB
JSON
[
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{
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"_id": "5babb6ee4eb7dd2c39b9671c",
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"title": "Apache OpenNLP Named Entity Recognition",
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"description": "Apache's open source natural language processing toolkit for named entity recognition (NER). See https://opennlp.apache.org/ for more information. This is the default pipeline used for NER.",
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"name": "opennlp",
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"parameters": {
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"cutoff": "integer",
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"iterations":" integer"
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}
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},
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{
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"_id": "5babb6ee4eb7dd2c39b9671d",
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"title": "SpaCy Named Entity Recognition",
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"description": "spaCy is a free open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more",
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"name": "spaCy",
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"parameters": {
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"n_iter": "integer",
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"dropout": "float"
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}
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},
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{
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"_id": "5babb6ee4eb7dd2c39b9671f",
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"title": "Stanford CoreNLP Named Entity Recognition",
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"description": "Stanford's natural language processing toolkit for named entity recognition (NER). See https://stanfordnlp.github.io/CoreNLP/ for more information.",
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"name": "corenlp",
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"parameters": {
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"max_left": "integer",
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"use_class_feature": [true, false],
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"use_word": [true, false],
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"use_ngrams": [true, false],
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"no_mid_ngrams": [true, false],
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"max_ngram_length": "integer",
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"use_prev": [true, false],
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"use_next": [true, false],
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"use_disjunctive": [true, false],
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"use_sequences": [true, false],
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"use_prev_sequences": [true, false],
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"use_type_seqs": [true, false],
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"use_type_seqs2": [true, false],
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"use_type_y_sequences": [true, false]
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}
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},
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{
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"_id": "5babb6ee4eb7dd2c39b96720",
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"title": "SimpleTransformers - Bio-ClinicalBERT",
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"description": "SimpleTransformers models.",
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"name": "simpletransformers",
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"parameters": {
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"training_batch_size": "integer",
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"num_train_epochs": "integer"
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}
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}
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]
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