Triple

T16799202
Position Surface form Disambiguated ID Type / Status
Subject Tijeras E408310 entity
Predicate nearMountain P31783 FINISHED
Object Sandia Crest E388903 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: Sandia Crest | Statement: [Tijeras, nearMountain, Sandia Crest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandia Crest
Context triple: [Tijeras, nearMountain, Sandia Crest]
  • A. Monte Vista
    Monte Vista was the former name of the city now known as Montclair in San Bernardino County, California.
  • B. Monte Vista
    Monte Vista is a residential suburb in the Northern Suburbs of Cape Town, South Africa.
  • C. Sandia Peak chosen
    Sandia Peak is a prominent mountain summit in the Sandia Mountains of central New Mexico, overlooking Albuquerque and popular for hiking, skiing, and panoramic views.
  • D. Sandia
    Sandia is a town in southeastern Peru that serves as an administrative and commercial center in the Andean highlands of the Puno Region.
  • E. Sandia Mountains
    The Sandia Mountains are a prominent rugged range in central New Mexico known for their pink-hued granite cliffs, hiking and skiing opportunities, and dramatic backdrop to the city of Albuquerque.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2abc430819080c1303eded5f416 completed April 18, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00ab1299ac81908e9f1eebc3424bb9 completed May 10, 2026, 3:58 p.m.
Created at: April 10, 2026, 5:22 a.m.