Triple

T18367055
Position Surface form Disambiguated ID Type / Status
Subject Surf Line E440074 entity
Predicate connectsCity P4245 FINISHED
Object Irvine 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: Irvine | Statement: [Surf Line, connectsCity, Irvine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irvine
Context triple: [Surf Line, connectsCity, Irvine]
  • A. Irvine chosen
    Irvine is a master-planned city in Orange County, California, known for its affluent residential communities, strong public schools, and concentration of technology and education industries.
  • B. Irvine
    Irvine is a coastal town in North Ayrshire, Scotland, known historically as a royal burgh and port on the Firth of Clyde.
  • C. Costa Mesa
    Costa Mesa is a city in Orange County, California, known for its major shopping centers, arts and theater district, and proximity to Southern California beaches.
  • D. El Cajon
    El Cajon is a suburban city in Southern California’s East County region, located just east of San Diego.
  • E. Anaheim
    Anaheim is a major city in Orange County, California, best known as the home of the Disneyland Resort and a significant hub for tourism and entertainment in the region.
  • 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5174f5f448190a1fc67d3039aadd9 completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:38 a.m.