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Paper Citation Record · LEDGER

Empirical Study of Zero-Shot NER with ChatGPT

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2310.10035.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2310.10035 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:32:36.978123Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T20:43:25.538391Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4d9970cd-e340-45d2-985b-11da336e632a · inbound

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition cites this paper.

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition Empirical Study of Zero-Shot NER with ChatGPT

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:43:25.541356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-23T20:40:09.530799Z digest=sha256:01cc8157498ae01182090ae9f860436403dd712d316554b79b66168875624c87

Observation 53b82de6-6fe6-4d5e-807c-7fdabd828fb3 · inbound

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language cites this paper.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Empirical Study of Zero-Shot NER with ChatGPT

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T18:18:35.211982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.211982Z digest=sha256:ffac9722af0f057cd82bf950d210faa18bdb891a4596e2ee8907e688808d1df8

Observation 4c3fc912-cc2d-400e-a067-ef65e08273f8 · inbound

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO cites this paper.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Empirical Study of Zero-Shot NER with ChatGPT

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T13:21:21.117394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:21.117394Z digest=sha256:364b0492759796c4d52bbaa6fb7fddfdfe265eb22bb2ffdf5fd1a06f42bfe45c

Observation dde5e7f4-4e37-4ada-9713-6fa0ccd848f7 · inbound

Token and Span Classification for Entity Recognition in French Historical Encyclopedias cites this paper.

Token and Span Classification for Entity Recognition in French Historical Encyclopedias Empirical Study of Zero-Shot NER with ChatGPT

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T11:19:56.718306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:19:56.718306Z digest=sha256:ee8375ba551513ac4d7a8817c93251249205f7ea0de03033893b063ba80a035c

Observation 1c18f898-fd63-4c72-9155-648cbeaf16f3 · inbound

MariNER: A Dataset for Historical Brazilian Portuguese Named Entity Recognition cites this paper.

MariNER: A Dataset for Historical Brazilian Portuguese Named Entity Recognition Empirical Study of Zero-Shot NER with ChatGPT

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T21:55:07.527447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:55:07.527447Z digest=sha256:b2ecccf0a5bf4fb538764ec4178cda323fcbe469d55175078205a1619f15356f

Observation 48808cc0-4fc0-4ad3-a423-b78cd927934c · inbound

Beyond the Basics: Leveraging Large Language Model for Fine-Grained Medical Entity Recognition cites this paper.

Beyond the Basics: Leveraging Large Language Model for Fine-Grained Medical Entity Recognition Empirical Study of Zero-Shot NER with ChatGPT

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:56:47.623181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T06:53:38.384323Z digest=sha256:bfe078ebb3c19f748a49ca0fa158626d4848db29ef32525ef62b0e1effaa97d2

Observation c6857075-148b-4519-820d-34cbefdba638 · inbound

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction cites this paper.

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction Empirical Study of Zero-Shot NER with ChatGPT

Reference 175

Resolution
unresolved
no resolver link, observed 2026-07-30T22:49:43.494497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T22:49:43.494497Z digest=sha256:d5aace1fed1f69c826aad99d0683dfacc37a503a5e9cdf353c1c1c6eb42ec484

Observation e6aa4bb9-e70f-4685-ad45-ffefb18a6cf0 · inbound

Enhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach cites this paper.

Enhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach Empirical Study of Zero-Shot NER with ChatGPT

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-14T04:32:36.978123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:32:36.978123Z digest=sha256:d978bed84e09235803ae619f0c44f44bad0d37fd2b6cf43a780f1c7e96460910