Triple

T11642061
Position Surface form Disambiguated ID Type / Status
Subject Skylanders: Trap Team E276682 entity
Predicate platform P1292 FINISHED
Object Kindle Fire E165151 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 Fire | Statement: [Skylanders: Trap Team, platform, Kindle Fire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kindle Fire
Context triple: [Skylanders: Trap Team, platform, Kindle Fire]
  • A. Kindle
    Kindle is Amazon’s line of portable e-readers designed primarily for reading digital books and other electronic publications.
  • B. Amazon Fire tablet chosen
    The Amazon Fire tablet is a line of budget-friendly Android-based tablets by Amazon, designed for media consumption, reading, and integration with Amazon’s digital services.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a260ab488190ab1c00d9850f3096 completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87deb3888190842bd61efd7b3989 completed April 26, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:39 p.m.