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Paper Citation Record · LEDGER

Knowledge prompt chaining for semantic modeling

As of 12 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2501.08540.

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

pith.paper-citation-record.v1
2501.08540 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:27:02.162167Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

  • verified exact1
  • verified fuzzy12
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e88965ff-7f53-449e-a0fc-b1c2119f958c · outbound

This paper cites imap: Discovering complex semantic matches between database schemas.

Knowledge prompt chaining for semantic modeling imap: Discovering complex semantic matches between database schemas

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.509347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.041452Z digest=sha256:da4ce970821f89911a3bf3b272af0354473b805f6405c8873306914d79e62971

Observation 4f709291-726f-43cb-9cc8-6fb662c51430 · outbound

This paper cites Knoblock, Pedro A.

Knowledge prompt chaining for semantic modeling Knoblock, Pedro A

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.495497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.046790Z digest=sha256:e8890854ae9e09fcb221468c8ae98c677e5deef9939cd40e03a8df29fca792d2

Observation 55b96cea-5c89-4373-a449-695e7edea6a0 · outbound

This paper cites Machine learning and constraint programming for relational-to-ontology schema mapping.

Knowledge prompt chaining for semantic modeling Machine learning and constraint programming for relational-to-ontology schema mapping

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.480697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.051331Z digest=sha256:08997ba66db92a2424b20ccd7de5b560ff30cd531fbbaef0c424d8dc950afbec

Observation 0c9a0677-9d13-49ac-a748-35203ab58986 · outbound

This paper cites Learning semantic models of data sources using probabilistic graphical models.

Knowledge prompt chaining for semantic modeling Learning semantic models of data sources using probabilistic graphical models

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.466878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.056508Z digest=sha256:24ddb06c175992cc5e247c25c2af5b93dfee19fd1e6add2834d5e34aae7694d2

Observation 494d2035-0209-41fd-9e52-5b62f6fbe004 · outbound

This paper cites Semi: A semantic modeling machine to build knowledge graphs with graph neural networks.

Knowledge prompt chaining for semantic modeling Semi: A semantic modeling machine to build knowledge graphs with graph neural networks

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.452772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.061545Z digest=sha256:e05a3a3c2b914b93902b74c2f3e30497faef4794526a75dd936c858d5ed79f16

Observation d7f75732-ebb1-4a62-8434-61229fc58284 · outbound

This paper cites Semantic labeling: a domain-independent approach.

Knowledge prompt chaining for semantic modeling Semantic labeling: a domain-independent approach

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.439265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.067242Z digest=sha256:4ffcb1435c8310d3a10c6246ecf0dc87ec99c7ae0f467ecbdfb0defb52a31a1a

Observation 9b06997b-c339-4eb5-8656-5f5a00df1d38 · outbound

This paper cites Evaluating approaches for supervised semantic labeling.

Knowledge prompt chaining for semantic modeling Evaluating approaches for supervised semantic labeling

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:27:02.315452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.073757Z digest=sha256:a1a4ff12ca8a46b5d7e4b3417caeae7ae09bc0577b25ed6db155e020e7c887ca

Observation 4d67ab32-2be6-4c16-854b-27e6773733cb · outbound

This paper cites Oyamada, Shinji Nakadai, and Takeshi Okadome.

Knowledge prompt chaining for semantic modeling Oyamada, Shinji Nakadai, and Takeshi Okadome

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.426137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.079100Z digest=sha256:9fad4e423e05d29f6062a0748e6a1aba027dac246e3e1fafc3842ea05f9e1173

Observation 190bb39d-b8e5-436f-9c8b-40196f5ed7fe · outbound

This paper cites Towards Better Serialization of Tabular Data for Few-shot Classification with Large Language Models.

Knowledge prompt chaining for semantic modeling Towards Better Serialization of Tabular Data for Few-shot Classification with Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.082954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.082954Z digest=sha256:fd00b2447384073b6f46a5ad490ac17e6580c9a54335fd0de00c5f323e736a84

Observation 0821d1d5-4a14-4fcb-9945-257ea8f1d0f6 · outbound

This paper cites Tabular representation, noisy operators, and impacts on table structure understanding tasks in llms.

Knowledge prompt chaining for semantic modeling Tabular representation, noisy operators, and impacts on table structure understanding tasks in llms

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.413304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.089324Z digest=sha256:8120e93c14e2f63221125cf10c50cdf57f5887b1e137161e82c4816853c0bb47

Observation 8075683f-7011-46da-ba15-40a535f2613c · outbound

This paper cites Tabllm: Few-shot classification of tabular data with large language models.

Knowledge prompt chaining for semantic modeling Tabllm: Few-shot classification of tabular data with large language models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.093426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.093426Z digest=sha256:ae2191880fee730eb53dec4eb07e087961e16aa67a74e675f5e0f4235882cb7c

Observation 6a8fb3ee-e80f-42ae-8fd5-0e2c4b27d44c · outbound

This paper cites TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning.

Knowledge prompt chaining for semantic modeling TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.097802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.097802Z digest=sha256:7f9b41c973f93f803774d2b481f33f3e6dbfa7fa4107e75849e3001253667950

Observation eec52578-ea74-424d-8bb4-7ce2c1fa1daa · outbound

This paper cites Language Models are Realistic Tabular Data Generators.

Knowledge prompt chaining for semantic modeling Language Models are Realistic Tabular Data Generators

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.102762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.102762Z digest=sha256:74e1a9ed6a2b422086ed1a37c688db587dbf1636ca1edb7f5984dc4b7350ef90

Observation 24148b29-1673-4d56-8206-e9c4bfe8c51c · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

Knowledge prompt chaining for semantic modeling Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.107523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.107523Z digest=sha256:1eefd45f8ba9dc009c11d58acb72d896c05db12b06c6016e6d91d07989f26e64

Observation e5be0eed-587e-42ea-9194-46912fed7373 · outbound

This paper cites Large Language Models are Complex Table Parsers.

Knowledge prompt chaining for semantic modeling Large Language Models are Complex Table Parsers

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.111868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.111868Z digest=sha256:b63584defc2fb5b0281ec3aa27e57e1db72c61a22dbb827ee32d9656b19879ed

Observation 7e2107dd-7ccd-4884-8e8f-ae118c5fca2b · outbound

This paper cites Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.

Knowledge prompt chaining for semantic modeling Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.116565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.116565Z digest=sha256:b941473856a9420a4c8c545afd8c7f7968787d93b79215572b8dc8688407f450

Observation d80f2f61-2fc8-4748-a391-38adc9110ef8 · outbound

This paper cites KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion.

Knowledge prompt chaining for semantic modeling KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.121769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.121769Z digest=sha256:ec239767b6a1cf0989382a6c255614e5eee68ef1fc3a73c59c7b80c395634184

Observation 51516138-a162-4c11-a2fa-cf5a64ce70f7 · outbound

This paper cites Knowledge Graph Large Language Model (KG-LLM) for Link Prediction.

Knowledge prompt chaining for semantic modeling Knowledge Graph Large Language Model (KG-LLM) for Link Prediction

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.126768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.126768Z digest=sha256:d4109fd8d75756fe93e9bc08a6421bf46795e8a830dc7cf27239dd8fa8c4aeff

Observation c8732d0b-53df-483f-a5c4-441d5cf60eb1 · outbound

This paper cites Soft knowledge prompt: Help external knowledge become a better teacher to instruct llm in knowledge-based vqa.

Knowledge prompt chaining for semantic modeling Soft knowledge prompt: Help external knowledge become a better teacher to instruct llm in knowledge-based vqa

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.384431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.131502Z digest=sha256:f14ce3777b75824ce1a81190310004b0317427660450e3b28306c41340031909

Observation 572b85b2-64ff-49ce-9401-7a230a9940f1 · outbound

This paper cites Sengamedu, and Christos Faloutsos.

Knowledge prompt chaining for semantic modeling Sengamedu, and Christos Faloutsos

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.136167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.136167Z digest=sha256:8554b8302fb9d80da34eced25cbb5f3bcb5160e1fb4d65ec1251ce64a0eadc06

Observation 8c2f2445-033b-4113-a44d-a367fe750229 · outbound

This paper cites Meta Prompting for AI Systems.

Knowledge prompt chaining for semantic modeling Meta Prompting for AI Systems

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T20:27:02.140677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:27:02.140677Z digest=sha256:61d38dd7fa3e587df9e805d4bf44653e7d3f510e98acc8bcd867be5e245aa2ed

Observation 5d07bff8-ebc5-4e37-b2fa-151c1b707bf5 · outbound

This paper cites All leaf nodes in the updated model must correspond to a table header in the data source, with names strictly aligned to ensure consistency.

Knowledge prompt chaining for semantic modeling All leaf nodes in the updated model must correspond to a table header in the data source, with names strictly aligned to ensure consistency

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.364403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.146695Z digest=sha256:54ff8714058a1c600fffac925b82442714cdf99f26e03a2e15daab46bd9eba9f

Observation 92c87ca0-4122-4f6e-ba50-dcc4662d648d · outbound

This paper cites an unresolved cited work.

Knowledge prompt chaining for semantic modeling Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-10T20:27:02.352355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.152121Z digest=sha256:cf1230703068540b984aea8916bccf2840a54eaab164df39f32f8c5a3a1cae92

Observation e2430297-5d0a-466f-8a56-09cb03483a2e · outbound

This paper cites • If the data source primarily focuses on personal information about artists without referencing their works, the crm:E39_Actor node is used.

Knowledge prompt chaining for semantic modeling • If the data source primarily focuses on personal information about artists without referencing their works, the crm:E39_Actor node is used

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.339447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.156436Z digest=sha256:d06292b3eabe613e7d49ba9322e771052ba79819f77572ccdb76221519aff4ad

Observation d18b164e-77a9-4c6e-9379-da542a8db12a · outbound

This paper cites Painting.

Knowledge prompt chaining for semantic modeling Painting

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:27:02.327344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:27:02.162167Z digest=sha256:954f5e9f3d4de5c532dcf553999e12a276bea1a0abe26d6a03a9065d753b8dc9

Pith citing papers

No inbound Pith citation observations are available.