Triple

T12447326
Position Surface form Disambiguated ID Type / Status
Subject UCLA Health Training Center E297434 entity
Predicate city P40 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: [UCLA Health Training Center, city, El Segundo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Segundo
Context triple: [UCLA Health Training Center, city, 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. Martinez-Ybor
    Martinez-Ybor is the surname of Vicente Martinez-Ybor, a prominent 19th-century Spanish-Cuban cigar manufacturer and founder of the Ybor City neighborhood in Tampa, Florida.
  • C. 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.
  • D. Las Matas
    Las Matas is a residential locality in the Community of Madrid, Spain, known as a suburban area closely linked to and bordering the municipality of Las Rozas de Madrid.
  • E. Lindavista
    Lindavista is a metro station in Mexico City serving the Lindavista neighborhood on the city's rapid transit network.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d90f18c819083a36ff4b9be4a20 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556839908190ac0401d373ad0fa9 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:56 p.m.