Triple

T20898631
Position Surface form Disambiguated ID Type / Status
Subject Mar Menor E514608 entity
Predicate adjacentTo P224 FINISHED
Object San Javier NE NERFINISHED

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 Javier | Statement: [Mar Menor, adjacentTo, San Javier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Javier
Context triple: [Mar Menor, adjacentTo, San Javier]
  • A. San Javier
    San Javier is a Chilean town known for its agricultural activity and wine production in the Maule Region.
  • B. San Javier chosen
    San Javier is a municipality in Spain’s Region of Murcia, known for hosting the Spanish Air and Space Force’s main officer training academy and its nearby coastal and lagoon areas on the Mar Menor.
  • C. San Javier
    San Javier is a town in the Mexican state of Baja California Sur, known for its historic mission and role as a regional cultural and religious center.
  • D. San Javier
    San Javier is a small settlement located on Quinchao Island in southern Chile’s Chiloé Archipelago.
  • E. Jerez de García Salinas
    Jerez de García Salinas is a historic colonial town and important agricultural and cultural center in the Mexican state of Zacatecas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f7ebe48190952a85547a0f31a1 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6e8f826788190b11008cc94b2a4e4 completed April 21, 2026, 3:03 a.m.
Created at: April 16, 2026, 12:47 p.m.