Triple

T21213531
Position Surface form Disambiguated ID Type / Status
Subject LAN Argentina E522777 entity
Predicate focusCity P164 FINISHED
Object Córdoba 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: Córdoba | Statement: [LAN Argentina, focusCity, Córdoba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Córdoba
Context triple: [LAN Argentina, focusCity, Córdoba]
  • A. Córdoba chosen
    Córdoba is a major city in central Argentina known for its industrial base, universities, and strategic military presence.
  • B. Córdoba
    Córdoba is a historic city in southern Spain renowned for its rich Moorish and medieval heritage, including the iconic Mezquita-Catedral.
  • C. Granada
    Granada is a historic city in southern Spain, renowned as the last stronghold of Muslim rule on the Iberian Peninsula and home to the famed Alhambra palace.
  • D. Granada
    Granada is a historic colonial city in western Nicaragua, known for its well-preserved Spanish architecture and location on the shores of Lake Nicaragua.
  • E. Granada
    Granada is a Colombian town and municipality in the Meta Department, known for its agricultural economy and role as a regional service center in the Llanos Orientales.
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7347088488190aa764b3f4bbac44d completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:38 p.m.