Search Results for author: Alon Eirew

Found 9 papers, 6 papers with code

Realistic Evaluation Principles for Cross-document Coreference Resolution

1 code implementation Joint Conference on Lexical and Computational Semantics 2021 Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

We point out that common evaluation practices for cross-document coreference resolution have been unrealistically permissive in their assumed settings, yielding inflated results.

Cross Document Coreference Resolution

Cross-document Coreference Resolution over Predicted Mentions

1 code implementation Findings (ACL) 2021 Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

Here, we introduce the first end-to-end model for CD coreference resolution from raw text, which extends the prominent model for within-document coreference to the CD setting.

Cross Document Coreference Resolution

WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia

2 code implementations NAACL 2021 Alon Eirew, Arie Cattan, Ido Dagan

To complement these resources and enhance future research, we present Wikipedia Event Coreference (WEC), an efficient methodology for gathering a large-scale dataset for cross-document event coreference from Wikipedia, where coreference links are not restricted within predefined topics.

Coreference Resolution Event Coreference Resolution

Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling

2 code implementations23 Sep 2020 Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance.

Cross Document Coreference Resolution Entity Cross-Document Coreference Resolution +1

Term Set Expansion based NLP Architect by Intel AI Lab

no code implementations EMNLP 2018 Jonathan Mamou, Oren Pereg, Moshe Wasserblat, Alon Eirew, Yael Green, Shira Guskin, Peter Izsak, Daniel Korat

We present SetExpander, a corpus-based system for expanding a seed set of terms into amore complete set of terms that belong to the same semantic class.

Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow

no code implementations26 Jul 2018 Jonathan Mamou, Oren Pereg, Moshe Wasserblat, Ido Dagan, Yoav Goldberg, Alon Eirew, Yael Green, Shira Guskin, Peter Izsak, Daniel Korat

We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class.

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