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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=sha256:9ec262d5a4c53d1eb67abd20093a7657a21c4a6bf347dea36a44aef62442a3ea

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=sha256:5555e9b4d5cbf3d37b07aeedc09537bf68331703edd830fbf6c4ccb7ab246e5f

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

Resolution
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=sha256:5fba1c1216f4f6934856520b2431d3fe2da7aec4d7baaef0cc81b9277088c586

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=sha256:34ea3a1a4cd4dddbd34fb281cbcbaa4966b5868ba76a9a8b4ef0f3c87759ee29

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=sha256:48e7b883ea5eab050bf19b9270fe289741e373e728646c0818980baae4970c78

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:e200c33afe5fa7f98189ce2411b21f55bdca1bbbf571eda40554e6b00e3bb991

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:b8aec6c1ee4ef1ed6d71017c87c8a981e72586ba78fac2e653aecec5e8963103

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:f977d25ef0032ad63ea5571d161bd429b64277ee2739c4fe8b3ed8a37668b842

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=sha256:9b071fc38729db2ccb285a1aa550b79bff0a80de00a6295a1d062b9e1b28dd6b

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=sha256:26fc0eef1ff28ca8b815a670202000d3aa503bed9db81401823f66761abc4931

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:fb01868f3886a5989d3944b42cab33b7e980a952e6b143ebec615bcff5d306a6

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=sha256:9c5fb1d9190f6f81a520de7cc62d0611db6755efc27bcbcaae0521af34f971bf

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=sha256:2075533f9d31bb953dac665adfc298d7baa460fe0cd7c4facb51ac7015f5d45f

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

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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:a18bc9cd1fd2d4b60b22d108ba7e9a488e68c710237673c5ea3c247b9b71d427

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=sha256:39cfb0da056dc9eda54118f970d818b87c7fa58f181212501eab377225fb321e

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=sha256:301a3c5cc046ab0551f1860c9cb893cbea59183c97f17512742a48a7ced4adf5

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:d84f230d335dac3b9ee2d1ffb5fbeb043acf41e4df8b12d67d1ae6f34293282d

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=sha256:03c27d4d77c10a167af06f7a429c059e206c1d219386c72fdf0a08a76ebfeacb

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=sha256:3253003acbcd7a08dda9d1541e7e594df4676b8e060d4d955936098595219a14

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=sha256:72ff108dd2aa5ce349ee25a02f97119cf47574d9c794b116eace867250c4444c

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=sha256:9ffd16ffa498b0a9f4498e998f225920d29d4d7bc754fc2cf92add81e6dffa9d

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=sha256:788706fb93a8bd15fe959bb3c91efeb9953c11922a9f278af450c5ef92933d72

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=sha256:43bd182c8575efb1043e1927bf795ca9e0dd913b73bf4b06db59df4c6e854d98

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=sha256:6ed6d7989f30b44b7c750b347ac46bf96e13fe2def74d453182b2703b4c53135

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=sha256:1f32f2b33e195f37fdf46d10f3f8bf02932e12eb350874578fa3286b8c0f9f37

Pith citing papers

No inbound Pith citation observations are available.