Triple

T14127433
Position Surface form Disambiguated ID Type / Status
Subject Diego de Deza E340069 entity
Predicate familyName P18 FINISHED
Object de Deza
de Deza is a Spanish surname historically associated with figures such as the Dominican friar and Grand Inquisitor Diego de Deza.
E1081385 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: de Deza | Statement: [Diego de Deza, familyName, de Deza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: de Deza
Context triple: [Diego de Deza, familyName, de Deza]
  • A. Zarda
    Zarda is a landmark U.S. Supreme Court case that held federal law prohibits employment discrimination based on sexual orientation.
  • B. Belouizdad
    Belouizdad is a district in Algiers, Algeria, known for its dense urban character and strong football culture.
  • C. DeMbare
    DeMbare is the popular nickname of Dynamos F.C., one of Zimbabwe’s most successful and widely supported football clubs.
  • D. Daule
    Daule is a town and canton in coastal Ecuador known for its rice production and location within the Guayas Province.
  • E. Kushma
    Kushma is a small town in central Nepal known for its dramatic suspension bridges and role as the administrative center of Parbat District.
  • 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: de Deza
Triple: [Diego de Deza, familyName, de Deza]
Generated description
de Deza is a Spanish surname historically associated with figures such as the Dominican friar and Grand Inquisitor Diego de Deza.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: de Deza
Target entity description: de Deza is a Spanish surname historically associated with figures such as the Dominican friar and Grand Inquisitor Diego de Deza.
  • A. Zarda
    Zarda is a landmark U.S. Supreme Court case that held federal law prohibits employment discrimination based on sexual orientation.
  • B. Belouizdad
    Belouizdad is a district in Algiers, Algeria, known for its dense urban character and strong football culture.
  • C. DeMbare
    DeMbare is the popular nickname of Dynamos F.C., one of Zimbabwe’s most successful and widely supported football clubs.
  • D. Daule
    Daule is a town and canton in coastal Ecuador known for its rice production and location within the Guayas Province.
  • E. Kushma
    Kushma is a small town in central Nepal known for its dramatic suspension bridges and role as the administrative center of Parbat District.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6098013c8190b1bac9d3fff60acd completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf0c833081908458e4eaee689df7 completed May 7, 2026, 6:50 p.m.
NEDg Description generation batch_69fce094bf3081909f7c0097dcb63398 completed May 7, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_69fce14ff8e48190b3b663d130d18418 completed May 7, 2026, 7 p.m.
Created at: April 9, 2026, 10:22 p.m.