Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Comprehensive Overview of Named Entity Recognition: Models, Domain-Specific Applications and Challenges
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.14084.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T22:40:44.349730Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T05:30:23.456663Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
15
pith, observed 2026-08-10T05:30:23.456663Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 8a4f87dd-d839-475f-a9c5-4dd5405d99d8 · inbound
Revisiting Projection-based Data Transfer for Cross-Lingual Named Entity Recognition in Low-Resource Languages cites this paper.
Revisiting Projection-based Data Transfer for Cross-Lingual Named Entity Recognition in Low-Resource Languages Comprehensive Overview of Named Entity Recognition: Models, Domain-Specific Applications and Challenges
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T22:40:44.349730Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b83fc8c0-d1e0-464d-8a45-d8f0ed976ac5 · inbound
FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework cites this paper.
FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework Comprehensive Overview of Named Entity Recognition: Models, Domain-Specific Applications and Challenges
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T12:24:19.775538Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 845b16e5-7110-4964-abdb-967fdeac13b3 · inbound
NER4all or Context is All You Need: Using LLMs for low-effort, high-performance NER on historical texts. A humanities informed approach cites this paper.
NER4all or Context is All You Need: Using LLMs for low-effort, high-performance NER on historical texts. A humanities informed approach Comprehensive Overview of Named Entity Recognition: Models, Domain-Specific Applications and Challenges
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T12:05:57.675044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.