Riccorl/transformer-srl
Reimplementation of a BERT based model (Shi et al, 2019), currently the state-of-the-art for English SRL. This model implements also predicate disambiguation.
This tool helps language researchers and computational linguists analyze the meaning of sentences by identifying who did what to whom, when, and where. You provide English sentences, and it outputs a structured breakdown of each verb's arguments and its specific meaning. It's designed for those who work with detailed linguistic analysis of text.
No commits in the last 6 months.
Use this if you need to automatically extract the semantic roles (agent, patient, location, etc.) for verbs in English sentences and clarify the precise meaning of each verb.
Not ideal if you need to analyze languages other than English or if you're looking for a simple keyword extractor.
Stars
71
Forks
9
Language
Perl
License
—
Category
Last pushed
Mar 19, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/Riccorl/transformer-srl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deeppavlov/AutoIntent
Automated machine learning for text classification
shushanxingzhe/transformers_ner
Add CRF or LSTM+CRF for huggingface transformers bert to perform better on NER task. It is very...
fran-martinez/bio_ner_bert
BERT finetuned on NER downstream tasks
liuyukid/transformers-ner
Pytorch-Named-Entity-Recognition-with-transformers
suamin/T2NER
T2NER: Transformers based Transfer Learning Framework for Named Entity Recognition (EACL 2021)