Triple

T19677400
Position Surface form Disambiguated ID Type / Status
Subject Shina language E472489 entity
Predicate closelyRelatedTo P37 FINISHED
Object Brokskat 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: Brokskat | Statement: [Shina language, closelyRelatedTo, Brokskat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brokskat
Context triple: [Shina language, closelyRelatedTo, Brokskat]
  • A. Brokskat chosen
    Brokskat is a Dardic language spoken in parts of northern Pakistan and India, closely related to the Shina language.
  • B. Krokkleiva
    Krokkleiva is a notable geographic feature in the municipality of Hole in Norway, known for its steep terrain and scenic surroundings.
  • C. Skrautvål
    Skrautvål is a small village in Nord-Aurdal Municipality in Innlandet county, Norway, known for its rural setting in the Valdres region and traditional Norwegian countryside character.
  • D. Blakset
    Blakset is a small village in the municipality of Stryn in Vestland county, western Norway.
  • E. Schleprock
    Schleprock is a perpetually gloomy, bad-luck-bringing character from the Flintstones universe, best known for his catchphrase “Wowzie wow wow.”
  • 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bceef881909c5b655af709c8c6 completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.