Triple

T8464431
Position Surface form Disambiguated ID Type / Status
Subject CV E200124 entity
Predicate standsFor P590 FINISHED
Object Chula Vista E38835 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: Chula Vista | Statement: [CV, standsFor, Chula Vista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chula Vista
Context triple: [CV, standsFor, Chula Vista]
  • A. Chula Vista chosen
    Chula Vista is a large coastal city in Southern California known for its diverse communities, rapid suburban growth, and proximity to both downtown San Diego and the U.S.–Mexico border.
  • B. El Cajon
    El Cajon is a suburban city in Southern California’s East County region, located just east of San Diego.
  • C. Carlsbad
    Carlsbad is a city in southeastern New Mexico known as the gateway to Carlsbad Caverns National Park.
  • D. Carlsbad
    Carlsbad is a coastal city in northern San Diego County, California, known for its beaches, family attractions like LEGOLAND California, and affluent residential communities.
  • E. Escondido
    Escondido is a city in northern San Diego County, California, known as one of the region’s older inland communities with a mix of suburban neighborhoods, agriculture, and historic downtown areas.
  • 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe4d05b2881909bddf58df0ee1143 completed March 31, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce39e0d7788190add03271c940e1ff completed April 2, 2026, 9:41 a.m.
Created at: March 30, 2026, 6:11 p.m.