Triple

T16944460
Position Surface form Disambiguated ID Type / Status
Subject San Felipe Province E411032 entity
Predicate hasCapitalCity P204 FINISHED
Object San Felipe E79916 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 Felipe | Statement: [San Felipe Province, hasCapitalCity, San Felipe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Felipe
Context triple: [San Felipe Province, hasCapitalCity, San Felipe]
  • A. 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.
  • 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 chosen
    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.
  • D. San Felipe
    San Felipe is a small coastal town in Mexico’s Yucatán Peninsula known for its colorful wooden houses, fishing traditions, and access to rich mangrove and wildlife areas.
  • E. San Felipe
    San Felipe is the historic colonial district of Panama City, Panama, known for its preserved architecture, plazas, and cultural landmarks.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cfb08da88190b07c32652bbc1534 completed April 18, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b3d9c648190bd0437c2f1e19b41 completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:31 a.m.