Paper Citation Record · LEDGER

Transforming Expert Knowledge into Scalable Ontology via Large Language Models

As of 23 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2506.08422.

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

pith.paper-citation-record.v1
2506.08422 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:21:03.194263Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:22:32.250270Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

verified exact2
verified fuzzy33
unresolved20
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5ccb874e-3c20-4daa-9707-18c9d164f73c · outbound

This paper cites Ontology-based knowledge management tools for knowledge sharing in organization—a review,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Ontology-based knowledge management tools for knowledge sharing in organization—a review,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.788377Z

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Observation ee27b2d4-a948-4dff-b1f4-8d08f531ee69 · outbound

This paper cites Healthcare Knowledge Graph Construction: State-of-the-art, open issues, and opportunities.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Healthcare Knowledge Graph Construction: State-of-the-art, open issues, and opportunities

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:21:03.337411Z

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Observation 65d21377-8ebd-429d-8d01-4d24f2ff8363 · outbound

This paper cites The behaviour change technique ontology: transforming the behaviour change technique taxonomy v1,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models The behaviour change technique ontology: transforming the behaviour change technique taxonomy v1,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.776905Z

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Observation 16144176-eae1-4bbe-8fd4-b34baedd51db · outbound

This paper cites Taxonomy development methods sciences–a systematic review,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Taxonomy development methods sciences–a systematic review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.765607Z

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Observation 2c7b2913-2399-4832-9005-17a6de58dcb6 · outbound

This paper cites Subsumption prediction for e-commerce taxonomies,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Subsumption prediction for e-commerce taxonomies,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.754920Z

Source-reported events for the cited work

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Observation b4fa6825-ea9c-400f-b2c0-2e4fc2d075ab · outbound

This paper cites Taxonomy of educational objectives: Teaching, learning, and assessing in the information and artificial intelligence era,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Taxonomy of educational objectives: Teaching, learning, and assessing in the information and artificial intelligence era,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.745111Z

Source-reported events for the cited work

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Observation 55190451-469c-40d9-ba26-6a4d4de27089 · outbound

This paper cites Euzenat, M.-E.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Euzenat, M.-E

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.735230Z

Source-reported events for the cited work

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Observation 1d54c6fe-bc21-4049-a09d-d6a03ad22f0c · outbound

This paper cites The prompt suite: interactive tools for ontology merging and mapping,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models The prompt suite: interactive tools for ontology merging and mapping,

Reference 8

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Source-reported events for the cited work

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Observation ba497e6c-3a64-4370-ac86-a193676407cc · outbound

This paper cites Deep learning for knowledge representation: Automating semantic analysis and ontology construction,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Deep learning for knowledge representation: Automating semantic analysis and ontology construction,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.718507Z

Source-reported events for the cited work

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Observation 65194418-2980-45b3-983a-85d85dc9af0b · outbound

This paper cites Learning to match ontologies on the semantic web,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Learning to match ontologies on the semantic web,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.704804Z

Source-reported events for the cited work

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Observation d6573201-c285-4ec3-a370-f79ce9055f3c · outbound

This paper cites Dis- tributed representations of words and phrases and their compositionality,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Dis- tributed representations of words and phrases and their compositionality,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.694764Z

Source-reported events for the cited work

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Observation f7562a6a-ea59-43bd-af08-504d98054f28 · outbound

This paper cites Glove: Global vectors for word representation,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Glove: Global vectors for word representation,

Reference 12

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Observation c3f72acd-5ea1-422b-90f9-6384aaacd770 · outbound

This paper cites A comprehensive survey of graph neural networks for knowledge graphs,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models A comprehensive survey of graph neural networks for knowledge graphs,

Reference 13

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Observation 0c5949c9-b43b-441d-ba07-134adba9b8fd · outbound

This paper cites Interpretable deep learning: Interpretation, interpretability, trustworthiness, and beyond,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Interpretable deep learning: Interpretation, interpretability, trustworthiness, and beyond,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.661752Z

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Observation 5632234d-0083-4941-8aac-c20dcf9b4b7f · outbound

This paper cites Ontologies in the era of large language models–a perspec- tive,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Ontologies in the era of large language models–a perspec- tive,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.650275Z

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Observation c463d811-6c61-4aa2-b988-62178ae042d7 · outbound

This paper cites Language models are few-shot learners,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Language models are few-shot learners,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.639013Z

Source-reported events for the cited work

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Observation 680341c9-0dd7-4cdf-a317-15f174e9bfde · outbound

This paper cites Llms4ol: Large language models for ontology learning,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Llms4ol: Large language models for ontology learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.627580Z

Source-reported events for the cited work

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Observation 21ff3cbc-eb0d-4a36-b03d-5b94ad87e2cd · outbound

This paper cites Ontogenix: Leveraging large language models for enhanced ontology engineering from datasets,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Ontogenix: Leveraging large language models for enhanced ontology engineering from datasets,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.615237Z

Source-reported events for the cited work

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Observation 2e28f4f2-92e2-4a59-b153-54961e335d9b · outbound

This paper cites Explain yourself! leveraging language models for commonsense reasoning,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Explain yourself! leveraging language models for commonsense reasoning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.605014Z

Source-reported events for the cited work

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Observation 466feda2-d36e-4ff2-be07-271b5cac9ea4 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Chain-of-thought prompting elicits reasoning in large language models,

Reference 20

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Observation 69a8c7da-26c2-4aae-b5a3-23ceea98f30e · outbound

This paper cites Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:21:03.067099Z

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Observation 3a021867-2828-4148-9d2f-40c67eae69b7 · outbound

This paper cites Large language models are zero-shot reasoners,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Large language models are zero-shot reasoners,

Reference 22

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Observation 6ceb5166-113a-4824-b79e-407d77c3fc0d · outbound

This paper cites AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Reference 23

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Observation 73342492-93d8-4059-b168-fc4b0516c867 · outbound

This paper cites Large language models are human-level prompt engineers,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Large language models are human-level prompt engineers,

Reference 24

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Observation 242bad32-66d0-46aa-8961-8aed1ced82d5 · outbound

This paper cites Large Language Models as Optimizers.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Large Language Models as Optimizers

Reference 25

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Observation 2be5f06f-d033-4bb2-a631-c39ed2427ae6 · outbound

This paper cites Connecting large language models with evo-lutionary algorithms yields powerful prompt optimizers.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Connecting large language models with evo-lutionary algorithms yields powerful prompt optimizers

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.568416Z

Source-reported events for the cited work

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Observation 3bed5237-b67d-4a41-a8b9-a3c9fd1cd29d · outbound

This paper cites Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 27

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Observation 004916eb-0554-49df-8582-dc35b3b04e4e · outbound

This paper cites Improving Consistency in Large Language Models through Chain of Guidance.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Improving Consistency in Large Language Models through Chain of Guidance

Reference 28

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Observation c7052d9b-9075-4f66-b5c5-8eb1b7ce4b8c · outbound

This paper cites In-context learning unlocked for diffusion models,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models In-context learning unlocked for diffusion models,

Reference 29

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Observation 57dd67bb-9617-4e58-b104-dd14de0f3029 · outbound

This paper cites Machine learning in automated text categorization,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Machine learning in automated text categorization,

Reference 30

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Observation 7420e6ab-8ed0-4714-8cac-477b9119f28f · outbound

This paper cites Baselines and bigrams: Simple, good sentiment and topic classification,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Baselines and bigrams: Simple, good sentiment and topic classification,

Reference 31

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Observation 24ef7672-18c6-4c81-8b64-3863a3ba4813 · outbound

This paper cites Chatgpt and finetuned bert: A comparative study for developing intelligent design support systems,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Chatgpt and finetuned bert: A comparative study for developing intelligent design support systems,

Reference 32

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Observation ca76c9a2-75c3-457a-ace0-1c7627977bf8 · outbound

This paper cites Paradigm shift presented by large language models (llm) in deep learning,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Paradigm shift presented by large language models (llm) in deep learning,

Reference 33

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Observation 65bc3e26-586a-4579-bc4d-85e1baee4ba4 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 34

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Observation 8ef1d1e0-37bf-4b06-b8ac-604df41d9f01 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 35

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This paper cites Language models of code are few-shot commonsense learners,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Language models of code are few-shot commonsense learners,

Reference 36

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Observation d5141d75-99f5-4435-9bca-f3311b5f4b17 · outbound

This paper cites Future of jobs report 2023,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Future of jobs report 2023,

Reference 37

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Observation f7ce049a-d2dd-4300-a0cb-491f63d731b5 · outbound

This paper cites Skos simple knowledge organization system reference,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Skos simple knowledge organization system reference,

Reference 38

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This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 39

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Observation d54d3e6a-473f-471f-baca-8f7dd6eb530a · outbound

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Potential and Perils of Large Language Models as Judges of Unstructured Textual Data

Reference 40

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This paper cites Reconciling Methodological Paradigms: Employing Large Language Models as Novice Qualitative Research Assistants in Talent Management Research.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Reconciling Methodological Paradigms: Employing Large Language Models as Novice Qualitative Research Assistants in Talent Management Research

Reference 41

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Observation 9dd393de-95b9-44bd-998c-a464bddb3844 · outbound

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Token-Budget-Aware LLM Reasoning

Reference 42

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach

Reference 43

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This paper cites Provide your reasoning in the rationale section, ensuring your assessment strictly aligns with the conceptual definitions provided.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Provide your reasoning in the rationale section, ensuring your assessment strictly aligns with the conceptual definitions provided

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.465091Z

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Observation b605abae-c9e7-4703-ac21-04a3f1cd1f8d · outbound

This paper cites - Usually Necessary: Very important, with rare exceptions.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models - Usually Necessary: Very important, with rare exceptions

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:03.454262Z

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Observation 53c275c9-ed65-475e-8b4a-f95d384c5e4a · outbound

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Out- put only ‘Required‘ or ‘Not Required‘

Reference 46

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

Reference 47

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

Reference 48

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

Reference 49

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Required

Reference 50

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

Reference 51

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

Reference 52

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Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

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This paper cites an unresolved cited work.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Unresolved cited work

Reference 54

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This paper cites For Claude 3.7 Sonnet specifically, our analysis included both standard inference operation and enhanced thinking mode with 10,000 reasoning tokens.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models For Claude 3.7 Sonnet specifically, our analysis included both standard inference operation and enhanced thinking mode with 10,000 reasoning tokens

Reference 55

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Pith citing papers

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Three Million Years Opposite State Data Retention in Partially Switched Wurtzite Ferroelectrics cites this paper.

Three Million Years Opposite State Data Retention in Partially Switched Wurtzite Ferroelectrics Transforming Expert Knowledge into Scalable Ontology via Large Language Models

Reference 152

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