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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=sha256:6be776ec2e26a7c7efe142b4fe9a5204c1fe17fe6e9bd17ccbfcfda585eee79a

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=sha256:2b6d12c122a787696c292056bf81afd6802774c08afda0e4641baf0a6312510d

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:cc9de4c150c40babccf2b35a4f12bda13969e96095338b37f0354e284c817d82

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=sha256:993b63d4ba74fd5033577c8116a9b66e3bb473f49b1697c08897940db472fcc2

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:a5ff63ade1c585ec511734a98dd9d49047948cb2a66869abffc327d235710054

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=sha256:48d6dc4e7f959edb587758615349d45417585aa1b5af6342e68493e767a6de77

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=sha256:5bd0338e5a914568ecc42d976da9a5658f2d7d9ccfa6cdea187416af1d9790c8

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:aa7e4ca9fb79564571571d6fc189db8d77410799419774a49cf6e7d302bf3e3b

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=sha256:1ff05aee2927c997139947b262f0258693fb6753878e3727bcb95a2738c69bda

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=sha256:8ac775dbd4c5c29d721f47c26d34a0cf91d39e7b6d169106b868c7663546e80e

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=sha256:2ba6d6abe1fc97466e84f21634c99a97408cc01189c5e58e09c112d2323701a1

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=sha256:9157dd96977090e2d8e269f4affe79384a61a1fe106b193725390e082f8d7778

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=sha256:6e33b9caba05062ec904a0c7d49b8e46963a2e2c680f6c02596b05e0870d345d

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:d56cfddd88350dd4021f58b46aa000bd93d444b7d928faca0918d017ae5297f9

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=sha256:93e26a99e8b4096adc13a1a320d3968722a4d3456cfeaff7174c4e86f0fbaa2e

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=sha256:10ee3e73e6a67cd9b7eabd92222c7b67371b075aa403a1719a69e6aca1be5fec

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=sha256:71192f62753b33e6a7f1b007455e4f10d1a2ab38a00f021a371f34ad70fafd34

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=sha256:3983185d4b8e93e45e8d87ab328448c537b8f6fcdb043d046f37b2cb5d488318

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=sha256:06b59c4a58eeb10eecb2be24dda16e3c4f7c160382c9136daf5e99b781555f2f

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=sha256:1feae8bca16c69ef5bc365736b7439e54d0edc6b0958c215973db007aae2f5e4

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=sha256:80f6e214195325af5af0de2762d2b6cca367041e19e549ebcedf6effd8e4883f

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:e5d81110239e8aac2e82d0dc05204f33ff93cb186cc869b680f1d79ee74f493e

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=sha256:406ac73fdf5547aedc43e7f016e7174977bc6a0002edfd252987351de9f563b6

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:c07d502379c17f44daf5b5652a2dec74b003e32e93037f6ba20a901ae958cc57

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=sha256:0ca039b31b16259164b3bf1e5e956ab7c5e0f47f729240648190e272159d1676

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=sha256:38cc24658b4f729cfba7b113a9d978db24114b8f07875eaf0cf1f875af387bae

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=sha256:5cc711795fd817b4e8dc2741ba9b49b338a28bc10f87e0786933c4d10e0a970e

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=sha256:794e4046ffe116c79555fe5466cf9565b609761c712467200553f250245c3e21

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:f6d6d642e3cd718fca8a58016ff21386478c05e428041ea83264440f1c31edbe

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=sha256:7cc21440e455e045e0c446c25e62163d6fa949c858b3c74e2e13af092041d135

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=sha256:148eac1f5aa42ce87d976759485b0b49976b21cf69f731655a35edb2ff68b910

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:f81a3030ecf8720b203b6535a48b67f18994492563f25fd616f69d7240325217

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=sha256:82e71e7710bca67cab5caa049f343b0207c7cfe4fc9b36b67297f02e142da73b

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:dad41bd2e6f4ed604a247af34c6d7169400200207430c194a1b3322a33c1c8fd

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=sha256:2bfea387af3bcd903f712756d1bb5f5d390f76800cbe9ea03e7cb5761ac5d961

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=sha256:03af1f6eccc9783eb2d3c5b4c96d4039b471e5983bfd5c7bcfadf519fe05a2f9

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=sha256:6aeb252fde1d256d5107d2e08c9abcd85e28ed6199efa30138441baba13e8486

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:dd45c7c837d6add3fd1f6d1705fff66c8e3a1c425cbbae5e150067dca10f3f66

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=sha256:697a678fd2692adaf54b8ac6cb7da0367cbd80068c83624e5114894d0060f05e

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=sha256:9f6cfd264312d89f3fbff1fcfa1b814c2fdc63943727b13eb7acd562162488f5

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:c9c3731c6b41aa9510bfb9e3885f5326b20dc456c6cdbeb814b169124674b436

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=sha256:001a525c2874737599ccdff4d2f0c18e7c713a2473c33464187a266ebac67e8a

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=sha256:516e4da6b3f67c2dba869abd4a36c841ef6b6944b490ad4cccb36e35abc9142e

Pith citing papers

No inbound Pith citation observations are available.