Triple

T1505291
Position Surface form Disambiguated ID Type / Status
Subject Westchester, Los Angeles E33885 entity
Predicate adjacentTo P224 FINISHED
Object El Segundo E52470 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: El Segundo | Statement: [Westchester, Los Angeles, adjacentTo, El Segundo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Segundo
Context triple: [Westchester, Los Angeles, adjacentTo, El Segundo]
  • A. El Segundo, California chosen
    El Segundo, California is a coastal city in Los Angeles County known for its concentration of aerospace, defense, and technology companies.
  • B. Toa Baja
    Toa Baja is a coastal municipality in northern Puerto Rico, known for its proximity to San Juan and its mix of urban, industrial, and residential areas.
  • C. Doral
    Doral is a discount cigarette brand produced by R.J. Reynolds Tobacco Company, known for its value-oriented positioning in the U.S. tobacco market.
  • D. Rosarito
    Rosarito is a coastal resort city in northern Baja California, Mexico, known for its beaches, tourism, and proximity to the U.S. border.
  • E. Lerdo
    Lerdo is a municipality and city in the Mexican state of Durango, known for its agricultural production and location within the Comarca Lagunera metropolitan area.
  • 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_69a885f352a4819099b24ff15489dede completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a88734508481909378bb3e86e13323 completed March 4, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad2945360c8190b20dfdf2f7be4fea completed March 8, 2026, 7:46 a.m.
Created at: March 4, 2026, 7:24 p.m.