Triple

T12426821
Position Surface form Disambiguated ID Type / Status
Subject John Spartan E296918 entity
Predicate settingOfActivity P1957 FINISHED
Object San Angeles E310823 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: San Angeles | Statement: [John Spartan, settingOfActivity, San Angeles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Angeles
Context triple: [John Spartan, settingOfActivity, San Angeles]
  • A. San Angeles chosen
    San Angeles is a fictional futuristic megacity formed from the merger of Los Angeles and San Diego in the science fiction film "Demolition Man."
  • B. Los Ángeles
    Los Ángeles is a mid-sized Chilean city known as an important commercial and agricultural center in the south-central part of the country.
  • C. San Cristóbal de los Ángeles
    San Cristóbal de los Ángeles is a neighborhood in Madrid, Spain, known in part for its local football club that helped develop future Real Madrid legend Raúl González during his youth.
  • D. Los Angeles
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • E. Pueblo de Los Ángeles
    Pueblo de Los Ángeles was the original Mexican-era settlement that evolved into the modern city of Los Angeles, California.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d7ccda08190be2ff1739c1c6855 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ea44a808190af2c5a6633120814 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:55 p.m.