Paper Citation Record · LEDGER

Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2304.11633.

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

pith.paper-citation-record.v1
2304.11633 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:55:04.220553Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:19:42.811549Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
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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 7e0acc3a-4930-42e7-9a7a-972a83e58b75 · inbound

OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models cites this paper.

OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-05-17T09:55:35.653112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 251c9f06-bd4c-462a-b623-1ffca731d191 · inbound

Enhancing Relation Extraction via Supervised Rationale Verification and Feedback cites this paper.

Enhancing Relation Extraction via Supervised Rationale Verification and Feedback Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T19:02:37.597769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eabd24fe-0b91-4f58-b7d0-c7d75d447c83 · inbound

OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System cites this paper.

OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T23:43:29.639350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bbbebae-fa20-4561-9893-738aa7e5bd26 · inbound

Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset cites this paper.

Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T23:39:19.566466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee9c1376-7cbc-4645-bcf1-bf7c8726faf3 · inbound

Improving TCM Question Answering through Tree-Organized Self-Reflective Retrieval with LLMs cites this paper.

Improving TCM Question Answering through Tree-Organized Self-Reflective Retrieval with LLMs Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T22:32:36.065814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1804c457-1c38-4478-a567-4f41cf376108 · inbound

Automated Construction of a Knowledge Graph of Nuclear Fusion Energy for Effective Elicitation and Retrieval of Information cites this paper.

Automated Construction of a Knowledge Graph of Nuclear Fusion Energy for Effective Elicitation and Retrieval of Information Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-22T20:52:06.340758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6ba504ff-be41-4679-92d5-5bffea510a95 · inbound

Evaluation of LLMs on Long-tail Entity Linking in Historical Documents cites this paper.

Evaluation of LLMs on Long-tail Entity Linking in Historical Documents Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T23:55:04.220553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5deecd63-f0d0-4852-81bb-aa73fa23ad7d · inbound

A Structured Literature Review on Traditional Approaches in Current Natural Language Processing cites this paper.

A Structured Literature Review on Traditional Approaches in Current Natural Language Processing Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T20:26:56.294397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94af5c65-9860-44f8-b72f-6dcc8917e18a · inbound

MPL: Multiple Programming Languages with Large Language Models for Information Extraction cites this paper.

MPL: Multiple Programming Languages with Large Language Models for Information Extraction Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T15:10:11.327750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 026e60e6-7076-48c7-890e-5f11520b64dd · inbound

Schema as Parameterized Tools for Universal Information Extraction cites this paper.

Schema as Parameterized Tools for Universal Information Extraction Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:50:46.509099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf9e6525-61cb-48c4-8be0-5c31f92e8d5b · inbound

ClimateViz: A Benchmark for Statistical Reasoning and Fact Verification on Scientific Charts cites this paper.

ClimateViz: A Benchmark for Statistical Reasoning and Fact Verification on Scientific Charts Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:09:11.330863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2db91223-aeb7-4237-b23d-dc636d28823c · inbound

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents cites this paper.

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:37:13.962184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 04a882f6-5f59-4b8a-949d-ade1d93afd64 · inbound

Investigating Student Interaction Patterns with Large Language Model-Powered Course Assistants in Computer Science Courses cites this paper.

Investigating Student Interaction Patterns with Large Language Model-Powered Course Assistants in Computer Science Courses Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T21:02:41.659555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 356981d0-b485-43fd-a123-6fa754807873 · inbound

Frugal Knowledge Graph Construction with Local LLMs: A Zero-Shot Pipeline, Self-Consistency and Wisdom of Artificial Crowds cites this paper.

Frugal Knowledge Graph Construction with Local LLMs: A Zero-Shot Pipeline, Self-Consistency and Wisdom of Artificial Crowds Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:21:04.128029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 41c97806-ea26-4058-b5af-7a26d7fc342d · inbound

How Small Can You Go? LoRA Fine-Tuning 270M-8B Models for Merchant Information Extraction in Financial Transactions cites this paper.

How Small Can You Go? LoRA Fine-Tuning 270M-8B Models for Merchant Information Extraction in Financial Transactions Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:37:24.401991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d014b5ce-891a-4a38-b885-fa858f3dd0a3 · inbound

Sub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction cites this paper.

Sub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 166

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:19:42.813783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8f57c9b8-e94d-400b-8634-3a82af5e8377 · inbound

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction cites this paper.

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:34:21.312573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f54de01d-95af-4649-9324-a4aed26f5b29 · 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 Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-30T22:49:43.082412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.