Triple

T6678061
Position Surface form Disambiguated ID Type / Status
Subject Región de Ñuble E151904 entity
Predicate hasCity P316 FINISHED
Object San Carlos E110192 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 Carlos | Statement: [Región de Ñuble, hasCity, San Carlos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Carlos
Context triple: [Región de Ñuble, hasCity, San Carlos]
  • A. San Carlos
    San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
  • B. San Carlos
    San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
  • C. San Carlos chosen
    San Carlos is a Chilean city known as an agricultural and commercial center in the Ñuble Region.
  • D. San Carlos
    San Carlos is a coastal component city in Negros Occidental, Philippines, known for its port, eco-tourism initiatives, and annual Pintaflores Festival.
  • E. San Félix
    San Félix is a major urban district of Ciudad Guayana in Bolívar State, Venezuela, known for its role in the region’s industrial and commercial activity.
  • 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_69c687f830bc81909eb8b04dbb8450b1 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0f53af48190b0b25b61c3531158 completed March 27, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7a78ab081909d904e4468293957 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:03 p.m.