Triple

T21096448
Position Surface form Disambiguated ID Type / Status
Subject Calero Creek E519779 entity
Predicate locatedIn P40 FINISHED
Object Santa Clara Valley 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: Santa Clara Valley | Statement: [Calero Creek, locatedIn, Santa Clara Valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Clara Valley
Context triple: [Calero Creek, locatedIn, Santa Clara Valley]
  • A. Santa Clara Valley chosen
    Santa Clara Valley is a region in Northern California that encompasses much of Silicon Valley, known for its high-tech industry, suburban communities, and proximity to the San Francisco Bay Area.
  • B. Santa Clara Canton
    Santa Clara Canton is an administrative subdivision in eastern Ecuador known for its location within the Amazonian Pastaza Province and its largely rural, rainforest-covered territory.
  • C. Santa Clara
    Santa Clara is a Silicon Valley city in California known for its high-tech industry presence, Levi’s Stadium, and Santa Clara University.
  • D. Santa Clara
    Santa Clara is a settlement located within the Arraiján District in Panama.
  • E. Santa Clara
    Santa Clara is a major city in central Cuba known as the capital of Villa Clara Province and a historic site of key battles in the Cuban Revolution.
  • 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_69e0b508d8dc81909be940dafe36c8f7 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e71b595cdc8190ba7a6f3f71d40c3f completed April 21, 2026, 6:38 a.m.
Created at: April 16, 2026, 2:52 p.m.