Triple

T15487144
Position Surface form Disambiguated ID Type / Status
Subject Sierra de Albarracín E377075 entity
Predicate capital P234 FINISHED
Object Albarracín E576914 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: Albarracín | Statement: [Sierra de Albarracín, capital, Albarracín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albarracín
Context triple: [Sierra de Albarracín, capital, Albarracín]
  • A. Albarracín chosen
    Albarracín is a historic hilltop town in eastern Spain renowned for its well-preserved medieval architecture and dramatic red sandstone setting.
  • B. Burriana
    Burriana is a coastal town in Spain’s Valencian Community known for its Mediterranean beaches and role as a holiday resort on the Costa del Azahar.
  • C. Montilla
    Montilla is a town in the province of Córdoba, Andalusia, Spain, known for its wine production and historical significance.
  • D. Alhué
    Alhué is a rural commune and town in central Chile known for its agricultural activities and traditional countryside character within the Santiago Metropolitan Region.
  • E. Daroca
    Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f8f71a08190a440ff19dcc65312 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82e376f08190b5ae9793a0381204 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 3:48 a.m.