Triple

T4481541
Position Surface form Disambiguated ID Type / Status
Subject Ñuble E100145 entity
Predicate containsCity P294 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: [Ñuble, containsCity, San Carlos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Carlos
Context triple: [Ñuble, containsCity, 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_69b34553cbe48190afa8ac1cac285b86 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356dddd488190bd5dedd3c0e77247 completed March 13, 2026, 12:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6377c694881909428b5cffb405c8d completed March 15, 2026, 4:37 a.m.
Created at: March 12, 2026, 11:36 p.m.