Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T22:13:33.868790Z
Paper Citation Record · LEDGER
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics
As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2502.09247.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
39 of 39 outbound references displayed
- verified exact2
- verified fuzzy31
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ac78cbee-430f-4666-9100-c8a2bdb12134 · outbound
This paper cites Distant supervision for relation extraction without labeled data.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Distant supervision for relation extraction without labeled data
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.254340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2e95abb9-0b7b-489f-b076-84cf1018b8ec · outbound
This paper cites A Frustratingly Easy Approach for Entity and Relation Extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics A Frustratingly Easy Approach for Entity and Relation Extraction
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:13:32.750235Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cdffef55-776c-498e-a63c-d7bae6174222 · outbound
This paper cites A novel pipelined end-to-end relation extraction framework with entity mentions and contextual semantic representation.Expert Systems with Applications, 228:120435, 2023.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics A novel pipelined end-to-end relation extraction framework with entity mentions and contextual semantic representation.Expert Systems with Applications, 228:120435, 2023
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.237228Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 82b7a5cd-6c24-4b1b-8373-92eb71440937 · outbound
This paper cites Cotype: Joint extraction of typed entities and relations with knowledge bases.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Cotype: Joint extraction of typed entities and relations with knowledge bases
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.222621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 86dc68a1-1924-418c-ba76-2ab748a99d3c · outbound
This paper cites Jointly identifying entities and extracting relations in encyclopedia text via a graphical model approach.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Jointly identifying entities and extracting relations in encyclopedia text via a graphical model approach
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.206501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6002f5fb-1037-4650-92da-0293eeb5ad36 · outbound
This paper cites Joint extraction of entities and relations based on a novel tagging scheme.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Joint extraction of entities and relations based on a novel tagging scheme
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.189288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e58095d7-7a1d-48c5-b342-6fdab66616c9 · outbound
This paper cites A novel global feature-oriented relational triple extraction model based on table filling.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics A novel global feature-oriented relational triple extraction model based on table filling
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.172931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation bbae3641-0380-408a-a4a6-26e4aaaf2456 · outbound
This paper cites Onerel: Joint entity and relation extraction with one module in one step.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Onerel: Joint entity and relation extraction with one module in one step
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.157097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2744466b-67e4-49f8-b541-ceffd78d27c4 · outbound
This paper cites Relation clas- sification via convolutional deep neural network.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Relation clas- sification via convolutional deep neural network
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.141999Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 02eaee13-62d3-42ff-b420-a0186a5875ab · outbound
This paper cites End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T22:13:34.331841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f5fc49ce-1b8e-43fa-9c3e-4690840739d7 · outbound
This paper cites Joint entity and relation extraction based on a hybrid neural network.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Joint entity and relation extraction based on a hybrid neural network
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:37.091931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ea0aba05-3564-49ff-9894-8ee4a918e0cc · outbound
This paper cites Span-based joint entity and relation extraction with transformer pre-training.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Span-based joint entity and relation extraction with transformer pre-training
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.894899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 73f1ae3a-acc7-44af-b522-83728d6ce5cc · outbound
This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics BERT: Pre-training of deep bidirectional transformers for language understanding
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.833188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a9e97b74-1c1b-4e8c-a1ce-528a1c9caec2 · outbound
This paper cites Span-based joint entity and relation extraction with attention-based span-specific and contextual semantic representations.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Span-based joint entity and relation extraction with attention-based span-specific and contextual semantic representations
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.670471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation eb803aa1-e2c0-4b97-9379-7afd3b1412fe · outbound
This paper cites A multi-gate encoder for joint entity and relation extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics A multi-gate encoder for joint entity and relation extraction
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.651076Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a911ae49-5943-409b-a954-38c65127c453 · outbound
This paper cites A novel cascade binary tagging framework for relational triple extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics A novel cascade binary tagging framework for relational triple extraction
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.455051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation dcff719c-d45f-4e4f-a94b-22c4d8d8c6ec · outbound
This paper cites Graphrel:Modelingtextasrelational graphs for joint entity and relation extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Graphrel:Modelingtextasrelational graphs for joint entity and relation extraction
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.281200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d39c94d1-7869-41aa-9dc4-cfe5783a630a · outbound
This paper cites Joint entity recognition and relation extraction as a multi-head selection problem.Expert Systems with Applications, 114:34–45, 2018.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Joint entity recognition and relation extraction as a multi-head selection problem.Expert Systems with Applications, 114:34–45, 2018
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.261813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a7392b25-1168-404e-8e67-9c1e4aeed919 · outbound
This paper cites Bert-based multi- head selection for joint entity-relation extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Bert-based multi- head selection for joint entity-relation extraction
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.169508Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 768c67cd-9a83-40c0-96ad-14df33ee004d · outbound
This paper cites Exploringprivileged features for relation extraction with contrastive student-teacher learning.IEEE Transactions on Knowledge and Data Engineering, 2022.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Exploringprivileged features for relation extraction with contrastive student-teacher learning.IEEE Transactions on Knowledge and Data Engineering, 2022
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:36.049421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6fc06de9-4c6e-4e74-8e24-c6c4ae642de8 · outbound
This paper cites TPLinker:Single-stagejointextractionofentitiesandrelationsthrough token pair linking.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics TPLinker:Single-stagejointextractionofentitiesandrelationsthrough token pair linking
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.940479Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d66b4045-f104-4ab4-b4fb-4651069403eb · outbound
This paper cites Attention is all you need.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Attention is all you need
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:13:33.162559Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92500ad4-0ebd-4f3e-831b-b51668d6a45a · outbound
This paper cites Joint entity and relation extraction with set prediction networks.IEEE Transactions on Neural Networks and Learning Systems, 2023.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Joint entity and relation extraction with set prediction networks.IEEE Transactions on Neural Networks and Learning Systems, 2023
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.831592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation abecc6d4-ff8c-4391-98fd-56a2a34033fa · outbound
This paper cites Linkner: Linking local named entity recognition models to large language models using uncertainty.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Linkner: Linking local named entity recognition models to large language models using uncertainty
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.665528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation aa25dbce-ef13-4e93-9914-2d470b89c311 · outbound
This paper cites Enhancing relation extraction from biomedical texts by large language models.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Enhancing relation extraction from biomedical texts by large language models
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.525973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ebf08c4f-10aa-40f2-8a27-0c0f4c99976f · outbound
This paper cites Introduction to the CoNLL-2004 shared task: Semantic role labeling.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Introduction to the CoNLL-2004 shared task: Semantic role labeling
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.468795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 97988b9e-6a44-4c24-b02e-f82405ce2833 · outbound
This paper cites Unified Structure Generation for Universal Information Extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Unified Structure Generation for Universal Information Extraction
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:13:33.603806Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d8465d0-5e1b-4928-bc4d-fceca699b013 · outbound
This paper cites Named entity recognition and relation extraction: State-of-the-art.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Named entity recognition and relation extraction: State-of-the-art
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.352687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7e2f5904-24b4-4b3b-95a1-bc5152cf294c · outbound
This paper cites Unified named entity recognition as word-word rela- tion classification.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Unified named entity recognition as word-word rela- tion classification
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.153204Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 860e5002-d958-452b-9898-0c974b6f6ef0 · outbound
This paper cites Kernel methods for relation extraction.Journal of machine learning research, 3(Feb):1083–1106, 2003.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Kernel methods for relation extraction.Journal of machine learning research, 3(Feb):1083–1106, 2003
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.071715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6075adef-f4c4-4e70-b140-71f36d3554f5 · outbound
This paper cites Modeling joint entity and relation extraction with table representation.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Modeling joint entity and relation extraction with table representation
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:35.000981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7313214e-d2bd-4b38-8e86-1609abeb9f08 · outbound
This paper cites Global Pointer: Novel Efficient Span-based Approach for Named Entity Recognition.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Global Pointer: Novel Efficient Span-based Approach for Named Entity Recognition
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:13:33.634512Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb432a91-11b4-40a2-95eb-8a46d1095b1b · outbound
This paper cites Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T22:13:34.067056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8285a7a5-2d4f-4526-b83e-17209c7ddd07 · outbound
This paper cites Generativere: Incorporating a novel copy mech- anism and pretrained model for joint entity and relation extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Generativere: Incorporating a novel copy mech- anism and pretrained model for joint entity and relation extraction
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:34.782269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b2eb9cc4-a66b-4f9d-9302-be09ad85e0f5 · outbound
This paper cites Semi-Supervised Classification with Graph Convolutional Networks.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Semi-Supervised Classification with Graph Convolutional Networks
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:13:33.650293Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e6f091a-29af-4f5f-adf0-6aa437f9732c · outbound
This paper cites Span-level model for relation extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Span-level model for relation extraction
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:34.616936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 51c0ea07-6939-436b-8ba5-1e4ca41ea71b · outbound
This paper cites GPT-NER: Named Entity Recognition via Large Language Models.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics GPT-NER: Named Entity Recognition via Large Language Models
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:13:33.660775Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11695af4-ea56-4e54-b362-ab2e63943571 · outbound
This paper cites Exploiting syntactico-semantic structures for rela- tion extraction.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Exploiting syntactico-semantic structures for rela- tion extraction
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:34.498226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3320851f-013a-4cdb-adea-42895f54aaad · outbound
This paper cites Boundary regression model for joint entity and relation extraction.Expert Systems with Applications, 229:120441, 2023.
The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics Boundary regression model for joint entity and relation extraction.Expert Systems with Applications, 229:120441, 2023
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T22:13:34.483133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.