Triple

T946855
Position Surface form Disambiguated ID Type / Status
Subject South Bay E20431 entity
Predicate contains P35 FINISHED
Object Gilroy E39931 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: Gilroy | Statement: [South Bay, contains, Gilroy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gilroy
Context triple: [South Bay, contains, Gilroy]
  • A. Gilroy chosen
    Gilroy is a city in Santa Clara County, California, known for its garlic production and as the southern endpoint of Caltrain commuter rail service.
  • B. Santa Rosa
    Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
  • C. Modesto
    Modesto is a mid-sized city in California’s Central Valley known for its agricultural economy, historic connection to the railroads, and as the hometown setting inspiration for George Lucas’s film "American Graffiti."
  • D. Santa Cruz
    Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
  • E. Monterey
    Monterey is a small rural town in Berkshire County, western Massachusetts, known for its scenic landscapes, forests, and lakes.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3bcad2481908b83575b2fb80d14 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad718263f08190b0f03d583abdad10 completed March 8, 2026, 12:54 p.m.
Created at: March 1, 2026, 7:40 p.m.