Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T12:12:49.213341Z
Paper Citation Record · LEDGER
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text
As of 16 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:1908.07721.
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 2026-08-16T06:30:59.297886+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
22 of 22 outbound references displayed
- verified exact2
- verified fuzzy17
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1f56b774-e1f1-4e05-8263-53e6b26c597c · outbound
This paper cites The emergence of national electronic health record architectures in the united states and australia: models, costs, and questions,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text The emergence of national electronic health record architectures in the united states and australia: models, costs, and questions,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.640663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6037a79c-f77b-4fb1-9f3b-cbb2e731413a · outbound
This paper cites Joint extraction of entities and relations based on a novel tagging scheme,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Joint extraction of entities and relations based on a novel tagging scheme,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.624907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3deff91f-ad78-4468-9231-93943ae56517 · outbound
This paper cites Joint type inference on entities and relations via graph convolutional networks,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Joint type inference on entities and relations via graph convolutional networks,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.606988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6ba6797b-e03e-42b9-bc50-4729e6535413 · outbound
This paper cites Joint entity and relation extraction based on a hybrid neural network,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Joint entity and relation extraction based on a hybrid neural network,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.587578Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0115e972-f516-4f63-bd8d-cb35052aa337 · outbound
This paper cites Fine-Grained Named Entity Recognition using ELMo and Wikidata.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Fine-Grained Named Entity Recognition using ELMo and Wikidata
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T12:12:49.306046Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 953339cc-9478-4998-9a9f-41e7c92f58fe · outbound
This paper cites Improving Relation Extraction by Pre-trained Language Representations.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Improving Relation Extraction by Pre-trained Language Representations
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T12:12:49.282773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fd8c2562-bfca-49f2-85c8-3ec893ccd321 · outbound
This paper cites BERT: Pre- training of deep bidirectional transformers for language understanding,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text BERT: Pre- training of deep bidirectional transformers for language understanding,
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:12:49.122961Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a7830ba9-aef4-4fb0-9795-0a7483581eeb · outbound
This paper cites Krishnan and V.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Krishnan and V
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.557755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 515c574d-b35d-4379-85dc-fd6837cb37fd · outbound
This paper cites Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: An annotation and machine learning study,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: An annotation and machine learning study,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.539548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e0c80ac9-5387-40b2-a72c-df9626dd1419 · outbound
This paper cites Incorporating dictionaries into deep neural networks for the chinese clinical named entity recognition,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Incorporating dictionaries into deep neural networks for the chinese clinical named entity recognition,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.519969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6b070d34-1c29-4167-bcb0-5f716faebd0d · outbound
This paper cites Utd: Classifying semantic relations by combining lexical and semantic resources,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Utd: Classifying semantic relations by combining lexical and semantic resources,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.501434Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 98818fef-b947-4d78-9741-ffa9d376f4c7 · outbound
This paper cites Kernel methods for relation extraction,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Kernel methods for relation extraction,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.482911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2f92daa4-e413-4e72-ad3a-301c60b92acf · outbound
This paper cites Automatic severity classification of coronary artery disease via recurrent capsule network,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Automatic severity classification of coronary artery disease via recurrent capsule network,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.463868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 71cc8fc4-c091-4b26-bc89-11187e8a2128 · outbound
This paper cites Incremental joint extraction of entity mentions and relations,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Incremental joint extraction of entity mentions and relations,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.426507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a61bb2ba-7330-4578-a4be-5e6bfe511261 · outbound
This paper cites A neural joint model for entity and relation extraction from biomedical text,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text A neural joint model for entity and relation extraction from biomedical text,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.408745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c0d868dd-7a1c-48c6-9037-4e9f41c725cf · outbound
This paper cites Attention is all you need,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Attention is all you need,
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:12:49.180130Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d44a82ac-af59-4a09-9631-538a5290b8e1 · outbound
This paper cites Bidirectional LSTM-CRF Models for Sequence Tagging.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Bidirectional LSTM-CRF Models for Sequence Tagging
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:12:49.185170Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca6dba32-3925-436e-bb38-15fe70807c50 · outbound
This paper cites A strategy on selecting performance metrics for classifier evaluation,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text A strategy on selecting performance metrics for classifier evaluation,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.379701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 17e0f938-22d1-4a50-a1bc-456ce0d8e148 · outbound
This paper cites Character-level neural network for biomedical named entity recognition,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Character-level neural network for biomedical named entity recognition,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.362057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2dc0c206-5dda-4569-b38b-049c7a582609 · outbound
This paper cites Chinese clinical named entity recognition using residual dilated convolutional neural network with conditional random field,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Chinese clinical named entity recognition using residual dilated convolutional neural network with conditional random field,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.344136Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 03d1f450-c4b6-478c-b5de-b449f1f1ed52 · outbound
This paper cites Relation extraction from clinical texts using domain invariant convolutional neural network,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Relation extraction from clinical texts using domain invariant convolutional neural network,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.443629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 67f55e05-5b02-434e-bc32-c56f1a4b3e33 · outbound
This paper cites Relation extraction: Perspective from convolutional neural networks,.
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text Relation extraction: Perspective from convolutional neural networks,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T12:12:49.325686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.