Triple

T9587799
Position Surface form Disambiguated ID Type / Status
Subject Aragon E231334 entity
Predicate containsCity P294 FINISHED
Object Calatayud E567892 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: Calatayud | Statement: [Aragon, containsCity, Calatayud]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calatayud
Context triple: [Aragon, containsCity, Calatayud]
  • A. Calatayud chosen
    Calatayud is a historic town in northeastern Spain known for its Mudéjar architecture and strategic location along the Jalón River.
  • B. Caseres
    Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
  • C. Daroca
    Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
  • D. Calahorra
    Calahorra is a historic city in northern Spain known for its Roman heritage and role as an agricultural and commercial center in the region of La Rioja.
  • E. Barbastro
    Barbastro is a historic town in the Aragon region of northeastern Spain, known for its wine production and medieval architecture.
  • 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_69ca848161688190a68d514a0a9d5129 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99f01ca08190afaa44645a58e918 completed April 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1618251c48190886190975dfde5ac completed April 4, 2026, 7:07 p.m.
Created at: March 30, 2026, 8:06 p.m.