Triple

T12724244
Position Surface form Disambiguated ID Type / Status
Subject Abra E304062 entity
Predicate hasMunicipality P847 FINISHED
Object San Quintin E241865 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 Quintin | Statement: [Abra, hasMunicipality, San Quintin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Quintin
Context triple: [Abra, hasMunicipality, San Quintin]
  • A. San Quintín chosen
    San Quintín is a coastal town in Baja California, Mexico, known for its agricultural production, volcanic landscapes, and growing tourism along the Pacific coast.
  • B. San Felipe
    San Felipe is a coastal municipality in the province of Zambales in the Philippines, known for its surfing beaches and laid-back rural atmosphere.
  • C. San Felipe
    San Felipe is a coastal town in Baja California, Mexico, known as a gateway to nearby natural attractions and desert and mountain landscapes.
  • D. San Felipe
    San Felipe is the historic colonial district of Panama City, Panama, known for its preserved architecture, plazas, and cultural landmarks.
  • E. San Felipe
    San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d964148f988190a4d0e7b41614fa64 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c85c6b88190bbdd94a43915a7a4 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:25 p.m.