Triple

T8329633
Position Surface form Disambiguated ID Type / Status
Subject Quintilian E195042 entity
Predicate birthPlace P1 FINISHED
Object Calahorra E629939 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: Calahorra | Statement: [Quintilian, birthPlace, Calahorra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calahorra
Context triple: [Quintilian, birthPlace, Calahorra]
  • A. Calahorra chosen
    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.
  • B. Alcañiz
    Alcañiz is a historic town in northeastern Spain’s Aragon region, known for its medieval architecture, strategic location, and role in the Spanish Civil War.
  • C. 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.
  • D. Calatayud
    Calatayud is a historic town in northeastern Spain known for its Mudéjar architecture and strategic location along the Jalón River.
  • E. Albarracín
    Albarracín is a historic hilltop town in eastern Spain renowned for its well-preserved medieval architecture and dramatic red sandstone setting.
  • 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_69ca82e87f2c8190bdb71ee29dfc642d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fb812508190aed8a283dacf712e completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc70723a48190a3e33908fc84fe59 completed April 2, 2026, 1:31 a.m.
Created at: March 30, 2026, 5:56 p.m.