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Paper Citation Record · LEDGER

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs

As of 21 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2505.08704.

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

pith.paper-citation-record.v1
2505.08704 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:52:10.578979Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d16bb810-0cf9-4f7b-9b6f-4a7dd1fc6145 · outbound

This paper cites The evolving use of electronic health records (ehr) for research,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs The evolving use of electronic health records (ehr) for research,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.889261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.486878Z digest=sha256:cca147927496b0578a2208764e0ee246608106d03249e48d8e7641c4e6d7ba0f

Observation 54a2145a-b614-4d6e-9a42-c0b415bd66bb · outbound

This paper cites Mining electronic health records (ehrs) a survey,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Mining electronic health records (ehrs) a survey,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.492275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.492275Z digest=sha256:4cb5dc69db059a4f8f98f1f2ceee08df867c5c710016d2d73c11a78fc93b1b71

Observation 1d377ea8-2441-4320-81f1-8a7b4d814620 · outbound

This paper cites Clinical named entity recognition: Challenges and opportunities,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Clinical named entity recognition: Challenges and opportunities,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.865902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.497014Z digest=sha256:fa61076a7143823e59c560fe82bf8d6c172f542d7e778c99ff726670567b0d16

Observation 7815324c-00de-4771-8395-d73d1551c96e · outbound

This paper cites GPT-NER: Named Entity Recognition via Large Language Models.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs GPT-NER: Named Entity Recognition via Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.501385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.501385Z digest=sha256:a5dd5ca79a65b41881afee39d0ed659e7d7fdb5b4d18a5c81992863bb6930e54

Observation ee893d76-82cc-4088-88aa-e11b4d40e346 · outbound

This paper cites Improving large language models for clinical named entity recognition via prompt engineering,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Improving large language models for clinical named entity recognition via prompt engineering,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.851987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.506401Z digest=sha256:306d080c30c4b1e02809e932ce18dd6ed4c075504ed647f7fd04962fa8de4c42

Observation d91b2d97-94a7-42e9-8b90-940f5d64fbfc · outbound

This paper cites A survey on recent named entity recognition and relationship extraction techniques on clinical texts,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs A survey on recent named entity recognition and relationship extraction techniques on clinical texts,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.837772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.511363Z digest=sha256:276860a5409c995cca9424338946d63db4f629ab0b6a52c66bf364394aadcc9d

Observation 9641fc4d-ac46-42be-96fe-fab85063b4a5 · outbound

This paper cites Clinical concept extraction: a methodology review,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Clinical concept extraction: a methodology review,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.823647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.516375Z digest=sha256:eca87ed7d4185418a5ee333d27062ee81ddf10dff8c2374afce3e0d671c0a6ec

Observation ac54c865-cbfe-4fb9-9348-6daca26213c1 · outbound

This paper cites Biobert based named entity recognition in electronic medical record,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Biobert based named entity recognition in electronic medical record,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.520769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.520769Z digest=sha256:a1a9faf38f4b18cf5c69aacc4b41f7b78ee1084e2efb88a57d695cab81fb268f

Observation 07c26633-78f3-4fff-a6b4-0c767ec0b743 · outbound

This paper cites Med-bert: A pretraining framework for medical records named entity recognition,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Med-bert: A pretraining framework for medical records named entity recognition,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.798704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.525024Z digest=sha256:8c2c6953b51017e3780a8573eabffef78602aed771229b0ee80e25a613822627

Observation 4a3c701c-ff0c-43c3-82f3-d29226f7a524 · outbound

This paper cites LLM on FHIR -- Demystifying Health Records.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs LLM on FHIR -- Demystifying Health Records

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.529252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.529252Z digest=sha256:dc7aef24638358f80fe3d004b59a53137500121462b97c944d1c07e3ade90f21

Observation e75bb70b-3496-4c63-8700-18737ca48fd3 · outbound

This paper cites How reliable ai chatbots are for disease prediction from patient complaints?.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs How reliable ai chatbots are for disease prediction from patient complaints?

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.782492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.534002Z digest=sha256:5f2bfadf316bbcade139b67b9a18627d2632a8ad623558488c11927ca7caa71c

Observation 9c26dc2b-6efc-4b65-86cd-d4c62d2e98ef · outbound

This paper cites Few-shot biomedical named entity recognition via knowledge-guided instance generation and prompt contrastive learning,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Few-shot biomedical named entity recognition via knowledge-guided instance generation and prompt contrastive learning,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.768481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.538374Z digest=sha256:49a5420ee38d9a522d90b91efbf3fb4f92c6bc343bc54fae6e0ce61b5ebae89d

Observation f49cfbaa-d292-48b6-a9c7-3f4bf6d86436 · outbound

This paper cites A critical assessment of using chatgpt for extracting structured data from clinical notes,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs A critical assessment of using chatgpt for extracting structured data from clinical notes,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.753892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.542610Z digest=sha256:6080a1a85211eebd80c2698d929efc16ab2dea5ba591340afd7c3b8b641fe6ae

Observation 55323f95-9601-464b-89ba-a30ae670f9dc · outbound

This paper cites 2010 i2b2/va challenge on concepts, assertions, and relations in clinical text,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs 2010 i2b2/va challenge on concepts, assertions, and relations in clinical text,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.739649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.547380Z digest=sha256:791002e479e359253b2221af6328959ce428b5e7c685de0d6b96fb9010c13886

Observation 1f2ee5c7-2e03-492b-8643-ad812864b60d · outbound

This paper cites GPT-4o System Card.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs GPT-4o System Card

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.552010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.552010Z digest=sha256:37ee4335b5c01634d7aebfb5670e71a00c0c46c0941f6728b41b5142b3a9261d

Observation cb620439-907a-4461-aef5-b30c7bc60366 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.556628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.556628Z digest=sha256:0df982e05faf8a0b04f20003fcebc380e562f04c189e8f62bf1b9f14804e7f1b

Observation c64dd1df-7d04-4c17-b1f9-767e7a6265e7 · outbound

This paper cites Alammar and M.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Alammar and M

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.725466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.561035Z digest=sha256:5c1c670df422abd32c17b42d576eda20388bd3512765991b6cfc6160c41f839b

Observation 7a680e97-d725-4c77-bdc5-0e89ceda63bb · outbound

This paper cites Lost in the middle: How language models use long contexts,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Lost in the middle: How language models use long contexts,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.565326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.565326Z digest=sha256:4e5700a563510766530d63c63aaacfffea6e6aef0a1d6557ad54f42dbff71e56

Observation b559abb0-f9da-4269-9c60-171dd2656373 · outbound

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

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Chain-of-thought prompting elicits reasoning in large language models,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.569866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.569866Z digest=sha256:c567ebe174932267925cd3495d95105fd8e1649e248c29131cc8f5df3fe1dbda

Observation fd7426cd-706d-4665-b6bb-d2a0815f6b44 · outbound

This paper cites Autocompletion of chief complaints in the electronic health records using large language models,.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Autocompletion of chief complaints in the electronic health records using large language models,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:52:10.691985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:52:10.574530Z digest=sha256:e22e344e9ed939e248a3a76f52a89cca94897e9c44674cbd7f7a4bf8b0cd41b6

Observation 9df20812-4257-414b-a090-f063301d9864 · outbound

This paper cites Publicly Available Clinical BERT Embeddings.

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Publicly Available Clinical BERT Embeddings

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:10.578979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:52:10.578979Z digest=sha256:b201071fc3e7ec9574153cd33615db08949d945df5cb26fcdddef0b036c10964

Pith citing papers

No inbound Pith citation observations are available.