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Constituency Parsing
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Constituency parsing aims to extract a constituency-based parse tree from a sentence that represents its syntactic structure according to a phrase structure grammar.
Example:
Sentence (S)
|
+-------------+------------+
| |
Noun (N) Verb Phrase (VP)
| |
John +-------+--------+
| |
Verb (V) Noun (N)
| |
sees Bill
Recent approaches convert the parse tree into a sequence following a depth-first traversal in order to be able to apply sequence-to-sequence models to it. The linearized version of the above parse tree looks as follows: (S (N) (VP V N)).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sooftware/nlp-attentions
https://github.com/sordonia/distance_parser
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
https://github.com/soumik12345/transformer.pytorch
https://github.com/souvikshanku/translit-former
https://github.com/stevinc/Transformer_Timeseries
https://github.com/studio-ousia/luke
https://github.com/sunnysinghnitb/text-corrector-software
https://github.com/sunnysinghnitb/text_corrector_software
https://github.com/svakulenk0/response_eval
https://github.com/swimmingCreative/DeepSpeechRecognition-master
https://github.com/tanjeffreyz/attention-is-all-you-need
https://github.com/tatp22/linformer-pytorch
https://github.com/tatp22/multidim-positional-encoding
https://github.com/tbmoon/LANL_Earthquake_Prediction
https://github.com/tcnguyen/bert
https://github.com/tcxdgit/MachineTranslation_t2t
https://github.com/tempra28/nmtrnng
https://github.com/tensorops/TransformerX
https://github.com/text-machine-lab/transformerpy
https://github.com/thanhlong1997/bert_quora
https://github.com/the-Quert/iNLPfun
https://github.com/theQuert/inlpfun
https://github.com/theamrzaki/text_summurization_abstractive_methods
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/thecodemasterk/BERT
https://github.com/thomaslu2000/incremental-parsing-representations
https://github.com/thumt/THUMT
https://github.com/thunlp-mt/ckd
https://github.com/tjrwlgns1198/ChatBot
https://github.com/tomdyer10/fake_news
https://github.com/tree-park/kor-to-eng-translation
https://github.com/tree-park/transformer_lm
https://github.com/truclycs/ocr_seq2seq
https://github.com/tshu-w/dbcopilot
https://github.com/tshu-w/llm4em
https://github.com/tvinith/bert
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.