Triple

T3227062
Position Surface form Disambiguated ID Type / Status
Subject Francisco Jiménez de Cisneros E67649 entity
Predicate deathPlace P21 FINISHED
Object Roa
Roa is a historic town in the province of Burgos, Spain, known for its medieval heritage and location in the Ribera del Duero wine region.
 E337404 NE FINISHED

How this triple was built (4 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: Roa | Statement: [Francisco Jiménez de Cisneros, deathPlace, Roa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Roa
Context triple: [Francisco Jiménez de Cisneros, deathPlace, Roa]
  • A. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • B. Ráquira
    Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
  • C. Coruripe
    Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
  • D. Vidigal
    Vidigal is a hillside favela neighborhood in Rio de Janeiro, Brazil, known for its striking ocean views, vibrant community, and growing cultural and tourism scene.
  • E. Arida
    Arida is a city in Japan known for its agricultural production, particularly high-quality citrus fruits, within Wakayama Prefecture.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Roa
Triple: [Francisco Jiménez de Cisneros, deathPlace, Roa]
Generated description
Roa is a historic town in the province of Burgos, Spain, known for its medieval heritage and location in the Ribera del Duero wine region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Roa
Target entity description: Roa is a historic town in the province of Burgos, Spain, known for its medieval heritage and location in the Ribera del Duero wine region.
  • A. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • B. Ráquira
    Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
  • C. Coruripe
    Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
  • D. Vidigal
    Vidigal is a hillside favela neighborhood in Rio de Janeiro, Brazil, known for its striking ocean views, vibrant community, and growing cultural and tourism scene.
  • E. Arida
    Arida is a city in Japan known for its agricultural production, particularly high-quality citrus fruits, within Wakayama Prefecture.
  • F. None of above. chosen

Provenance (5 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaeb5e67c819082070d108d3613ba completed March 8, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b26262af848190a918f3a606bfa616 completed March 12, 2026, 6:51 a.m.
NEDg Description generation batch_69b264e25bd48190978a289565854297 completed March 12, 2026, 7:01 a.m.
NED2 Entity disambiguation (via description) batch_69b265cd3fcc8190bc56bbf2de229386 completed March 12, 2026, 7:05 a.m.
Created at: March 8, 2026, 3:08 p.m.