Triple

T6312315
Position Surface form Disambiguated ID Type / Status
Subject Córdoba Province E141531 entity
Predicate hasCity P316 FINISHED
Object Montilla E445600 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: Montilla | Statement: [Córdoba Province, hasCity, Montilla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montilla
Context triple: [Córdoba Province, hasCity, Montilla]
  • A. Montilla chosen
    Montilla is a town in the province of Córdoba, Andalusia, Spain, known for its wine production and historical significance.
  • B. Utrera
    Utrera is a historic town in southern Spain’s Andalusia region, known for its rich flamenco heritage, traditional bullfighting culture, and well-preserved architecture.
  • C. Albarracín
    Albarracín is a historic hilltop town in eastern Spain renowned for its well-preserved medieval architecture and dramatic red sandstone setting.
  • D. Sanlúcar de Guadiana
    Sanlúcar de Guadiana is a small Spanish village in the province of Huelva, Andalusia, situated on the banks of the Guadiana River opposite the Portuguese town of Alcoutim.
  • E. Mairena del Aljarafe
    Mairena del Aljarafe is a suburban municipality in Andalusia, Spain, located near the city of Seville and known for its residential character and growing services sector.
  • 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_69c008d00efc8190a36c05b4b4a3bf4b completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0649ea98c819086509e175812c6c0 completed March 22, 2026, 9:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64ba5b0bc8190aefa07c77c99be83 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:28 p.m.