Triple

T9077997
Position Surface form Disambiguated ID Type / Status
Subject Juan Crespí E217536 entity
Predicate placeOfActivity P1527 FINISHED
Object California E26 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: California | Statement: [Juan Crespí, placeOfActivity, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: California
Context triple: [Juan Crespí, placeOfActivity, California]
  • A. California
    California is a popular Volkswagen camper van model known for its integrated living amenities and suitability for road trips and outdoor travel.
  • B. Kalifornia
    Kalifornia is a 1993 neo-noir road thriller film that follows a journalist couple researching serial killers while unknowingly traveling with one.
  • C. California, United States chosen
    California, United States is a large and populous U.S. state on the West Coast known for its diverse geography, major technology and entertainment industries, and cultural and economic influence.
  • D. CA
    CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
  • E. CA
    CA is the commonly used abbreviation for Club Africain, a major Tunisian multi-sport club best known for its football team based in Tunis.
  • 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc95c7d3688190a4c1c6a92965eae4 completed April 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d02fed4b6081908be3ee570e27abc5 completed April 3, 2026, 9:23 p.m.
Created at: March 30, 2026, 7:12 p.m.