Triple

T15513645
Position Surface form Disambiguated ID Type / Status
Subject Project Gutenberg E368775 entity
Predicate distributionFormat P218 FINISHED
Object Kindle E31214 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kindle | Statement: [Project Gutenberg, distributionFormat, Kindle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kindle
Context triple: [Project Gutenberg, distributionFormat, Kindle]
  • A. Kindle chosen
    Kindle is Amazon’s line of portable e-readers designed primarily for reading digital books and other electronic publications.
  • B. Kindle Cloud Reader
    Kindle Cloud Reader is a web-based application by Amazon that lets users read and manage their Kindle ebooks directly in a browser without needing a dedicated device or app.
  • C. Kobo e-readers
    Kobo e-readers are a line of digital reading devices known for their wide format support, integration with public libraries, and openness compared to many competing platforms.
  • D. Nook e-reader
    The Nook e-reader is Barnes & Noble’s line of electronic reading devices designed for purchasing, downloading, and reading digital books and other publications.
  • E. Kobo Writing Life
    Kobo Writing Life is Kobo's self-publishing platform that enables independent authors to publish and distribute their ebooks globally through the Kobo ecosystem.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85a1794cc8190b0b428716296e63e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e04031e62c8190953b61207142af15 completed April 16, 2026, 1:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d4edee481908382ca5cd266f7b0 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:01 a.m.