Triple

T3269824
Position Surface form Disambiguated ID Type / Status
Subject Guanajuato E68616 entity
Predicate hasCity P316 FINISHED
Object Salamanca E231945 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: Salamanca | Statement: [Guanajuato, hasCity, Salamanca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salamanca
Context triple: [Guanajuato, hasCity, Salamanca]
  • A. Salamanca
    Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
  • B. Salamanca chosen
    Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
  • C. Salamanca
    Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
  • D. Alcalá de Henares
    Alcalá de Henares is a historic Spanish city east of Madrid, renowned as the birthplace of Miguel de Cervantes and for its well-preserved university and medieval architecture.
  • E. Alcalá la Real
    Alcalá la Real is a historic town in southern Spain known for its imposing La Mota fortress and strategic location between Granada and Jaén.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adaff349148190beae8c0994b7ad83 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3c4323c819087a7c6e6c8a7b030 completed March 12, 2026, 5:11 p.m.
Created at: March 8, 2026, 3:09 p.m.