Triple

T4446421
Position Surface form Disambiguated ID Type / Status
Subject Valdres E96299 entity
Predicate contains P35 FINISHED
Object Vang E433534 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: Vang | Statement: [Valdres, contains, Vang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vang
Context triple: [Valdres, contains, Vang]
  • A. Vang chosen
    Vang is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, traditional farming communities, and outdoor recreation opportunities.
  • B. Kavalan
    Kavalan is an indigenous Austronesian language of Taiwan, traditionally spoken by the Kavalan people on the island’s northeastern coast.
  • C. Vega Alta
    Vega Alta is a coastal municipality in northern Puerto Rico known for its beaches, agricultural areas, and proximity to the San Juan metropolitan region.
  • D. Volnay
    Volnay is a renowned wine-producing village in Burgundy, France, celebrated for its elegant, aromatic red wines made primarily from Pinot Noir.
  • E. Viré
    Viré is a renowned wine-producing village in France’s Mâconnais region, best known for its high-quality white Burgundy wines made primarily from Chardonnay.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d1eba08190899d0a3c1684ce4e completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b613850eb88190b689a632b0e2b374 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:32 p.m.