ACE05
Related Papers
J-NERD: Joint Named Entity Recognition and Disambiguation with Rich Linguistic Features
AbstractMethods for Named Entity Recognition and Disambiguation (NERD) perform NER and NED in two separate stages. Therefore, NED may be penalized with respect to precision by NER false positives, and …...
A Unified MRC Framework for Named Entity Recognition
AbstractThe task of named entity recognition (NER) is normally divided into nested NER and flat NER depending on whether named entities are nested or not. Models are usually separately developed …...
Let’s Stop Incorrect Comparisons in End-to-end Relation Extraction!
AbstractDespite efforts to distinguish three different evaluation setups (Bekoulis et al., 2018), numerous end-to-end Relation Extraction (RE) articles present unreliable performance comparison to previous work. In this paper, we first …...
Pre-training Entity Relation Encoder with Intra-span and Inter-span Information
AbstractIn this paper, we integrate span-related information into pre-trained encoder for entity relation extraction task. Instead of using general-purpose sentence encoder (e.g., existing universal pre-trained models), we introduce a span …...
ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction
AbstractCurrent state-of-the-art systems for joint entity relation extraction (Luan et al., 2019; Wad-den et al., 2019) usually adopt the multi-task learning framework. However, annotations for these additional tasks such as …...
Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention
AbstractEvent detection has long been troubled by the trigger curse: overfitting the trigger will harm the generalization ability while underfitting it will hurt the detection performance. This problem is even …...
HySPA: Hybrid Span Generation for Scalable Text-to-Graph Extraction
Text-to-Graph extraction aims to automati- cally extract information graphs consisting of mentions and types from natural language texts. Existing approaches, such as table filling and pairwise scoring, have shown impressive …...
Unsupervised Domain Adaptation for Event Detection using Domain-specific Adapters
Due to the multi-dimensional variation of tex- tual data, detection of event triggers from new domains can become a lot more challenging. This prompts a need to research on domain …...
A Multi-Gate Encoder for Joint Entity and Relation Extraction
Abstract“Named entity recognition and relation extraction are core sub-tasks of relational triple extraction. Recent studies have used parameter sharing or joint decoding to create interaction between these two tasks. However, …...
Rescue Implicit and Long-tail Cases: Nearest Neighbor Relation Extraction
AbstractRelation extraction (RE) has achieved remarkable progress with the help of pre-trained language models. However, existing RE models are usually incapable of handling two situations: implicit expressions and long-tail relation …...
Revisiting Event Argument Extraction: Can EAE Models Learn Better When Being Aware of Event Co-occurrences?
AbstractEvent co-occurrences have been proved effective for event extraction (EE) in previous studies, but have not been considered for event argument extraction (EAE) recently. In this paper, we try to …...