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Paper Citation Record · LEDGER

Improving Multi-Word Entity Recognition for Biomedical Texts

As of 16 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:1908.05691.

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

pith.paper-citation-record.v1
1908.05691 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:10:20.786183Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

44 of 44 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5befdd38-3e2c-4fde-a457-e92f6a4f021a · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:21.628212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0f494dc3-9a59-44dc-9ae3-9d2a83b368ab · outbound

This paper cites A single abbreviation can be interpreted as two different entities according to the context.

Improving Multi-Word Entity Recognition for Biomedical Texts A single abbreviation can be interpreted as two different entities according to the context

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.609153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.369459Z digest=sha256:47be33a173fb70b2ec5301859003dc603941daa870be17f7b4d3615993c8b266

Observation 532ce9ce-2b74-4643-9880-e0d3578fe6d2 · outbound

This paper cites For example, “myc-c” refers to the name of a gene or protein.

Improving Multi-Word Entity Recognition for Biomedical Texts For example, “myc-c” refers to the name of a gene or protein

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.586040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.374804Z digest=sha256:47ef0efea4cc89c1da55d6ff4c97f7d2bf4f245dfb0e81454ab592b127fd5807

Observation 6c29d354-833b-43e1-a2f0-37d532d04e56 · outbound

This paper cites For example, CASP3, caspase-3, and CPP32 denote the same entity [2].

Improving Multi-Word Entity Recognition for Biomedical Texts For example, CASP3, caspase-3, and CPP32 denote the same entity [2]

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.568657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.379956Z digest=sha256:e23d0e84bae29fb31009f910af74196b89b8af140131f3aeb397716840db4110

Observation b0cfa843-2145-4f0e-a44b-d021770119f3 · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:21.548547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.386221Z digest=sha256:a955b7411055bd39a75b03726a5176024360f970accb27c0ca901620cb6fb17d

Observation e86624e2-7a51-49cd-afc3-f40ab0f36686 · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:21.531484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.392025Z digest=sha256:ff46719933cfb3da8e37ae30c03afd3f9d93778eadcd24cc95bddd248b29604c

Observation 714b1405-11af-4ef2-9ce8-5f5440850f5b · outbound

This paper cites BP” (blood pressure) corresponding to laboratory test is a BioNE that occurs in “control BP.

Improving Multi-Word Entity Recognition for Biomedical Texts BP” (blood pressure) corresponding to laboratory test is a BioNE that occurs in “control BP

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.511918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.398515Z digest=sha256:c69bf39a76058cd823e8b6f07f5ba0e9ed5ce77e5b5a7c8c387d2865a9ab96c6

Observation 4aaafb1b-da10-4650-bc1f-ecae8669de4a · outbound

This paper cites Approaches for Bio NER varies from dictionary -based, rule -based, Machine Learning (ML) to hybrid approaches.

Improving Multi-Word Entity Recognition for Biomedical Texts Approaches for Bio NER varies from dictionary -based, rule -based, Machine Learning (ML) to hybrid approaches

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.490991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.404068Z digest=sha256:f43692975283a5d9c4042ebf7722549523294c0194276b3e5dbc90c311e7248d

Observation 24060177-b41c-4216-bb08-415f62f4821b · outbound

This paper cites The T cell surface molecule CD28 binds to ligands on accessory cells and APCs ,.

Improving Multi-Word Entity Recognition for Biomedical Texts The T cell surface molecule CD28 binds to ligands on accessory cells and APCs ,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.472024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.410251Z digest=sha256:4bc84116e7204bee29b5b5883a56b608a56a23a3e7eaefc7ca44725b81ea4265

Observation 54d0d655-5418-4fe5-86ae-87c84e651cab · outbound

This paper cites These approaches depend es sentially on extracting feature set used for training the appropriate algorithm.

Improving Multi-Word Entity Recognition for Biomedical Texts These approaches depend es sentially on extracting feature set used for training the appropriate algorithm

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.454718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.418038Z digest=sha256:622f547f5a199ed5712bf49ed7b2bc6b8c8156674532bfd4774262bedaf4d2e6

Observation 344cc849-9fe9-45c0-af72-b6a809a14ddd · outbound

This paper cites human proximal sequence element -binding transcription factor.

Improving Multi-Word Entity Recognition for Biomedical Texts human proximal sequence element -binding transcription factor

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.438630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.423419Z digest=sha256:2f2378fa8aff122afb4f53297869328928165262edb481980785270060bbba91

Observation d27a9ffe-aa36-4bae-a45a-6cdd3e324218 · outbound

This paper cites human",.

Improving Multi-Word Entity Recognition for Biomedical Texts human",

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.420248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.429384Z digest=sha256:a41a848f725f99aa680f686819056aeacdc482e0060fe7c371ce9f58a3f54f61

Observation 74bfb2cd-b7e7-4392-bc2e-bb619fdfb0f5 · outbound

This paper cites To evaluate FROBES, we used a Bi-LSTM based model as a baseline system on JNLPBA and i2b2 datasets.

Improving Multi-Word Entity Recognition for Biomedical Texts To evaluate FROBES, we used a Bi-LSTM based model as a baseline system on JNLPBA and i2b2 datasets

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.401580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.439197Z digest=sha256:ace2e1dbbb8bc64534656300b1a3095246edb64216b65b0e725f9cf46d05fd0d

Observation b1086ebb-7389-4125-b709-6dc6bc762b9d · outbound

This paper cites and Sundheim B.: Message Understanding Conference -6: a brief history.

Improving Multi-Word Entity Recognition for Biomedical Texts and Sundheim B.: Message Understanding Conference -6: a brief history

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.385327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.445156Z digest=sha256:555b77733ed0fb021a95102ac5b38908c4664dbfe7693605ae9c1940265e2bde

Observation 7da1a732-213e-4f5a-8485-17f74381a5ab · outbound

This paper cites Tanabe and W.

Improving Multi-Word Entity Recognition for Biomedical Texts Tanabe and W

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.370588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.451063Z digest=sha256:f3b06baf330d8b0c8c4b236b800ff961e15428bff79f7bab7bb731ecdcba0fd5

Observation e112946c-9479-4a52-8b87-91c988d4cda6 · outbound

This paper cites Ananiadou and J.

Improving Multi-Word Entity Recognition for Biomedical Texts Ananiadou and J

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.355614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.461185Z digest=sha256:675072646fc737f63ee49f1cd7a7c8169af785fa1f668ede965c617f5f22a9ea

Observation 8337c33f-af1b-4000-ac68-d24dc14693f5 · outbound

This paper cites and Zhang Z.: A generic classifier -ensemble approach for biomedical named entity recognition, Advances in Knowledge Discovery and Data Mining, 86-97.

Improving Multi-Word Entity Recognition for Biomedical Texts and Zhang Z.: A generic classifier -ensemble approach for biomedical named entity recognition, Advances in Knowledge Discovery and Data Mining, 86-97

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.339533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.471030Z digest=sha256:25d7e333f4e1f7085914ee223ed8fbcae9d4378a4b23ecaf6186e48e2e6c8fb3

Observation 5b2d1819-300c-4e4e-855d-0758a0c5de5e · outbound

This paper cites BMC bioinformatics, 18(11), 385, (2017).

Improving Multi-Word Entity Recognition for Biomedical Texts BMC bioinformatics, 18(11), 385, (2017)

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.322200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.481046Z digest=sha256:e5c8df32a6a5d87fdb638bc6e16b9fe835b27ca7269e26ea342d0084e82ef306

Observation 814774d2-d262-4163-9df6-77694aa67c20 · outbound

This paper cites In International Conference on Advanced Intelligent Systems and Informatics (pp.

Improving Multi-Word Entity Recognition for Biomedical Texts In International Conference on Advanced Intelligent Systems and Informatics (pp

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.305217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.488184Z digest=sha256:8c45ff5c8d63920c7bfbd01851b459fbacfb517752e3e34591a5ec1fa617261f

Observation a44b9c8f-4378-4d3a-b7df-dd10ca5f29ed · outbound

This paper cites IEEE transactions on neural networks , 5(2), 157-166, (1994).

Improving Multi-Word Entity Recognition for Biomedical Texts IEEE transactions on neural networks , 5(2), 157-166, (1994)

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.287436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.499399Z digest=sha256:48a5c529d90c4fab64b4205d2addda8a8c99e1d9188862e02d02d8ff05d0542d

Observation fd68fe0e-26b4-426b-9225-0f7b7db28075 · outbound

This paper cites I n International Conference on Machine Learning, pp.

Improving Multi-Word Entity Recognition for Biomedical Texts I n International Conference on Machine Learning, pp

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.268824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.511964Z digest=sha256:b0b74317190cf6dad8b5add6bf3533cd8ad5e98957c56791394b2c6d813676a9

Observation b34e5778-0f1e-48a3-b6ff-011faed78562 · outbound

This paper cites and Jürgen Schmidhuber.

Improving Multi-Word Entity Recognition for Biomedical Texts and Jürgen Schmidhuber

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.250726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.519709Z digest=sha256:cd450db487e23531f40fd0b052dae39f887f179f7fc07c8f9180eb866dd5c09c

Observation 55a0202c-4ddf-4647-bc57-7d1744a68a97 · outbound

This paper cites Neural Networks, 18(5), 602-610, (2005).

Improving Multi-Word Entity Recognition for Biomedical Texts Neural Networks, 18(5), 602-610, (2005)

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.232388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.528055Z digest=sha256:c72f5409d5a3c2ddcbd981d3268c1f9b407ecf23f196ed36759fa41473c11d8f

Observation 96c2f4a5-aa31-4bfb-8dc4-59a323f921d3 · outbound

This paper cites and Frank G.: Tagging unknown proper names using decision trees.

Improving Multi-Word Entity Recognition for Biomedical Texts and Frank G.: Tagging unknown proper names using decision trees

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.213909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.534747Z digest=sha256:7ca18475657f7d26d94da901ffd8cb70070ec43c1cf5055bdb1437a9fa9d712a

Observation 7db5ab9c-aef1-4e16-8640-a80afa2079e0 · outbound

This paper cites 173-179, (1999).

Improving Multi-Word Entity Recognition for Biomedical Texts 173-179, (1999)

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.194954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.541524Z digest=sha256:2f03705c6c18f86bf4809bbd9eb9b9d88b9bba0e43f5dc8e32d20e0476527191

Observation 94ae2ef3-03af-4dd4-ac49-9be3d48ecac9 · outbound

This paper cites Computational Linguistics and Chinese Language Processing vol.

Improving Multi-Word Entity Recognition for Biomedical Texts Computational Linguistics and Chinese Language Processing vol

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.178575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.547441Z digest=sha256:e8e4d3cea556436655485a7770f449fae5394215a83eb429af746a387dba52b8

Observation 3bbf87ae-eea7-4d75-a651-048acde4b7d9 · outbound

This paper cites and Lu, B.-L.: Effective tag set selection in Chinese word segmentation via conditional random field modeling.

Improving Multi-Word Entity Recognition for Biomedical Texts and Lu, B.-L.: Effective tag set selection in Chinese word segmentation via conditional random field modeling

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.159634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.552335Z digest=sha256:9a5640eee1d6f3a6fa068f287e9537cc3136f699c3c8a1a468abfa77bb7bd376

Observation 43e02c3d-c798-4bca-ab61-211dada84237 · outbound

This paper cites "Design challenges and misconceptions in named entity recognition.

Improving Multi-Word Entity Recognition for Biomedical Texts "Design challenges and misconceptions in named entity recognition

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.142135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.557363Z digest=sha256:077002818a252bab419dc8f6958390ef86c86ea809c1b17623a1234fd61e49cb

Observation ef115697-4f5a-4efa-b7e2-e877169abb44 · outbound

This paper cites C., Okazaki N., Miwa M.

Improving Multi-Word Entity Recognition for Biomedical Texts C., Okazaki N., Miwa M

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.125653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.691561Z digest=sha256:aa5f9ad2f83cb8ef0f7131eeeb641241e9857a4bf17964687c7e67a57fa12f0f

Observation ccafa7f5-1564-4455-9e18-ac6f2e7329e9 · outbound

This paper cites Marcus: Text chunking using transformation-based learning.

Improving Multi-Word Entity Recognition for Biomedical Texts Marcus: Text chunking using transformation-based learning

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.108976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.698886Z digest=sha256:e51c251bc1f1a1961fba1141e0db6d70107e6dd4e8be05f0854471134519eeb9

Observation aff92b47-98d4-4f74-9696-d6fbad702303 · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:21.091950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.705201Z digest=sha256:cbafce323f3db4391f67d6d21fa527c9ece99a4f8e6024ffe59bc32241cc7a9e

Observation 72f6173d-d219-4a0d-909b-e0b95d9d4010 · outbound

This paper cites In Proceedings of the second meeting of the North American Chapter of ACL on Language Technologies, pp.

Improving Multi-Word Entity Recognition for Biomedical Texts In Proceedings of the second meeting of the North American Chapter of ACL on Language Technologies, pp

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.065574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.710742Z digest=sha256:f7539f6fb7b697ad9ffbfd2f430c0ed983bccfdc6f4719fd72e59b8739a40aa6

Observation d1fe3f2c-71d4-4197-a183-9c5a757ca60e · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:21.046969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.715734Z digest=sha256:2465ac95fefdc38ea1e024a9f8525a76fe8abaab480a897beef2af61a4d27d40

Observation 0af2913f-3a0c-4618-80e8-1fdb7dbd7e09 · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:21.029826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.721422Z digest=sha256:3cbe55c60f727f2bb0ebbafa10ee29e80dfb1a659b46c689612c9ebcae6642af

Observation b5422b44-f9f3-4680-af80-25a192bfd62a · outbound

This paper cites He and M.

Improving Multi-Word Entity Recognition for Biomedical Texts He and M

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:21.009636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.727627Z digest=sha256:0ce504e0a01795ecd355a4046c8bbc2ea66f1ab0bf9d0b973f48c81e60730645

Observation 171eb030-f10a-457a-8029-8d06e59518b7 · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:20.991408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.733847Z digest=sha256:26a092254e8746dd507e30c65512cca67ad8ea5c45bda50a94555b4c00af7d93

Observation cbddd450-cf4b-4fc1-8575-a240095a6c39 · outbound

This paper cites and Korhonen A.: A neural network multi-task learning approach to biomedical named entity recognition.

Improving Multi-Word Entity Recognition for Biomedical Texts and Korhonen A.: A neural network multi-task learning approach to biomedical named entity recognition

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.970079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.739151Z digest=sha256:6e23563917eb7616b0a7d016242f1f1145ac38ba38246ea74655ec4d99a9e9e2

Observation f11effb6-0937-4f93-898d-7536e34e3812 · outbound

This paper cites In Pacific symposium on biocomputing, vol.

Improving Multi-Word Entity Recognition for Biomedical Texts In Pacific symposium on biocomputing, vol

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.949260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.745234Z digest=sha256:79d259b1076992509dd415d70ff27c0c296f6c1740303d03b6d48fb6d5925b29

Observation 298f3723-e44b-4540-a9b2-85bf34e54bb6 · outbound

This paper cites Information Processing & Management, vol.

Improving Multi-Word Entity Recognition for Biomedical Texts Information Processing & Management, vol

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.927414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.752194Z digest=sha256:6a1bfc3a1e7b328908d025fbd03c3f533d54015f723320c826de72637ffabdd5

Observation 3cbd5559-fdd7-4135-9ce8-ece73d9e64db · outbound

This paper cites L., and Hamada A.

Improving Multi-Word Entity Recognition for Biomedical Texts L., and Hamada A

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.906231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.760011Z digest=sha256:dd07a975e20f8c7831d2fb61a0e8ea2825b0675262866ec033c3dd01063b4542

Observation 9bde1a3c-e5ab-4d81-996f-1cf08242d327 · outbound

This paper cites Computer methods and programs in biomedicine vol.

Improving Multi-Word Entity Recognition for Biomedical Texts Computer methods and programs in biomedicine vol

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.887748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.765991Z digest=sha256:58a7fadb09797ac0085fdb352d43ec4459dd32e1edeaa416a9aa78f49e4e0567

Observation dce7f24d-ea0f-44cf-aefe-7384a94e1775 · outbound

This paper cites an unresolved cited work.

Improving Multi-Word Entity Recognition for Biomedical Texts Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:10:20.868062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.771764Z digest=sha256:7f350b61cbaa0edeb8ad0d1e8b62bf580c2add9dc56a760053c58cc451dc46d4

Observation 5d045f56-c1c7-4c1c-a493-75b4fcf15f46 · outbound

This paper cites South, Shuying Shen and Scott L.

Improving Multi-Word Entity Recognition for Biomedical Texts South, Shuying Shen and Scott L

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.850813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.781080Z digest=sha256:9735a535d5202ff0c591e1aaa79049a6285bb07b1895ce111183b08bf0369417

Observation b1c1fef6-e3c2-40d6-a52e-82aacb6aba7f · outbound

This paper cites D., Ohta T., Tateisi Y.

Improving Multi-Word Entity Recognition for Biomedical Texts D., Ohta T., Tateisi Y

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:10:20.832626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:10:20.786183Z digest=sha256:c4494a8f66061d9a918c2064cecd8096436a8fdee2ec87811601924a3a373a38

Pith citing papers

No inbound Pith citation observations are available.