Triple

T21809477
Position Surface form Disambiguated ID Type / Status
Subject Sancy Massif E538432 entity
Predicate hasSkiResort P1981 FINISHED
Object Super-Besse NE NERFINISHED

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: Super-Besse | Statement: [Sancy Massif, hasSkiResort, Super-Besse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Super-Besse
Context triple: [Sancy Massif, hasSkiResort, Super-Besse]
  • A. Super-Besse chosen
    Super-Besse is a French ski and mountain resort in the Massif Central known for its winter sports facilities and outdoor recreational activities.
  • B. Bessa
    Bessa was an ancient Greek city located in the region of Opuntian Locris in central Greece.
  • C. Barbel
    Barbel is a feminine given name, commonly used as a diminutive or variant of names like Barbara in German-speaking regions.
  • D. The Super
    The Super is a 2017 American thriller film about a former cop who becomes the superintendent of a New York City apartment building where tenants begin mysteriously disappearing.
  • E. The Super
    The Super is a 1991 American comedy film starring Joe Pesci as a slum landlord forced to live in one of his own rundown buildings, with Bruno Kirby in a supporting role.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c473f0f8819086c9d1b4a143bd67 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f07cc4809c8190853e2777a1f573d4 completed April 28, 2026, 9:24 a.m.
Created at: April 16, 2026, 6:53 p.m.