Triple

T10797327
Position Surface form Disambiguated ID Type / Status
Subject San Luis Province E254744 entity
Predicate capital P234 FINISHED
Object San Luis E366492 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 Luis | Statement: [San Luis Province, capital, San Luis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Luis
Context triple: [San Luis Province, capital, San Luis]
  • A. San Luis
    San Luis is a municipality and town in western Cuba known for its agricultural activities within Pinar del Río Province.
  • B. San Luis chosen
    San Luis is a province in central Argentina known for its mountainous landscapes, arid climate, and role in the country’s early independence era.
  • C. San Luis
    San Luis is a town on the southeastern coast of Menorca in Spain’s Balearic Islands, known for its whitewashed architecture and nearby beaches.
  • D. San Luis
    San Luis is a coastal municipality in the Philippine province of Batangas known for its agricultural economy and small-town rural character.
  • E. San Luis
    San Luis is a municipal barrio (district) of the mountainous town of Aibonito in central Puerto Rico.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73333dc4081909faa40c10bce2735 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7b050ec8190b75877d5724c2aec completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:17 p.m.