Triple

T11329475
Position Surface form Disambiguated ID Type / Status
Subject Far Far Away E268303 entity
Predicate featuresCharacter P626 FINISHED
Object Gingy E864566 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: Gingy | Statement: [Far Far Away, featuresCharacter, Gingy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gingy
Context triple: [Far Far Away, featuresCharacter, Gingy]
  • A. Gingy chosen
    Gingy is the wisecracking, resilient gingerbread man character from the Shrek franchise, known for his high-pitched voice and memorable comic moments.
  • B. Onich
    Onich is a small village on the shores of Loch Linnhe in the Scottish Highlands, known for its scenic coastal views and proximity to Glencoe and Fort William.
  • C. Hagonoy
    Hagonoy is a coastal municipality in the province of Bulacan in the Philippines, known for its fishing industry and aquaculture.
  • D. Kiga
    Kiga is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda, near the Great Lakes region of East Africa.
  • E. Hikarigaoka
    Hikarigaoka is a large residential neighborhood in Tokyo known for its extensive public housing complexes, parks, and planned urban layout.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9e330008190b75490efde01dc59 completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e526236b688190aca4f2400a12e726 completed April 19, 2026, 6:59 p.m.
Created at: April 8, 2026, 9:32 p.m.