A survey on extraction of causal relations from natural language text
As an essential component of human cognition, cause–effect relations appear frequently in
text, and curating cause–effect relations from text helps in building causal networks for …
text, and curating cause–effect relations from text helps in building causal networks for …
Learn from relational correlations and periodic events for temporal knowledge graph reasoning
Reasoning on temporal knowledge graphs (TKGR), aiming to infer missing events along the
timeline, has been widely studied to alleviate incompleteness issues in TKG, which is …
timeline, has been widely studied to alleviate incompleteness issues in TKG, which is …
Joint biomedical entity and relation extraction with knowledge-enhanced collective inference
Compared to the general news domain, information extraction (IE) from biomedical text
requires much broader domain knowledge. However, many previous IE methods do not …
requires much broader domain knowledge. However, many previous IE methods do not …
Constructing a disease database and using natural language processing to capture and standardize free text clinical information
S Raza, B Schwartz - Scientific Reports, 2023 - nature.com
The ability to extract critical information about an infectious disease in a timely manner is
critical for population health research. The lack of procedures for mining large amounts of …
critical for population health research. The lack of procedures for mining large amounts of …
A novel pipelined end-to-end relation extraction framework with entity mentions and contextual semantic representation
The mainstream method of end-to-end relation extraction is to jointly extract entities and
relations by sharing span representation, which, however, may cause feature conflict. The …
relations by sharing span representation, which, however, may cause feature conflict. The …
Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach
S Raza, B Schwartz - BMC Medical Informatics and Decision Making, 2023 - Springer
Background Extracting relevant information about infectious diseases is an essential task.
However, a significant obstacle in supporting public health research is the lack of methods …
However, a significant obstacle in supporting public health research is the lack of methods …
Dynamic modeling cross-modal interactions in two-phase prediction for entity-relation extraction
Joint extraction of entities and their relations benefits from the close interaction between
named entities and their relation information. Therefore, how to effectively model such cross …
named entities and their relation information. Therefore, how to effectively model such cross …
A Span-based Multi-Modal Attention Network for joint entity-relation extraction
Joint extraction of entities and their relations not only depends on entity semantics but also
highly correlates with contextual information and entity types. Therefore, an effective joint …
highly correlates with contextual information and entity types. Therefore, an effective joint …
Flat multi-modal interaction transformer for named entity recognition
Multi-modal named entity recognition (MNER) aims at identifying entity spans and
recognizing their categories in social media posts with the aid of images. However, in …
recognizing their categories in social media posts with the aid of images. However, in …
Learning implicit entity-object relations by bidirectional generative alignment for multimodal ner
The challenge posed by multimodal named entity recognition (MNER) is mainly two-fold:(1)
bridging the semantic gap between text and image and (2) matching the entity with its …
bridging the semantic gap between text and image and (2) matching the entity with its …