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Paper Citation Record · LEDGER

Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1604.00734.

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

pith.paper-citation-record.v1
1604.00734 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:32:42.218904Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-04T21:23:29.581828Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a377a1f0-ab85-4f32-8ac4-8b80b884064e · inbound

Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation cites this paper.

Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T13:32:42.218904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:32:42.218904Z digest=sha256:ea219281c1e7a4da91fa51924c3dc27e545413495835eb04a85174fb9d4c575c

Observation 0f5ddfca-8f24-4472-bde2-3ee1ad3cdd9a · inbound

Learning Dynamic Context Augmentation for Global Entity Linking cites this paper.

Learning Dynamic Context Augmentation for Global Entity Linking Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-14T05:06:00.405314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:06:00.405314Z digest=sha256:9c25cbcea48a3b0c89df38f963e9a96d753f911dde941fb2213abe37b527cd44

Observation c6c25c27-de62-41d3-a4fb-5d62295f42af · inbound

JEL: A Novel Model Linking Knowledge Graph entities to News Mentions cites this paper.

JEL: A Novel Model Linking Knowledge Graph entities to News Mentions Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:23:29.666888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-04T21:23:28.286542Z digest=sha256:9356a50f7835c7a84ad121028ace45de332d6eeb3badfdb32e47326e12679677