Triple

T15346368
Position Surface form Disambiguated ID Type / Status
Subject Fulgencio Yegros E366928 entity
Predicate title P38 FINISHED
Object Don
Don is a Spanish honorific title historically used to denote respect and high social status, often associated with nobility or distinguished gentlemen.
 E1151760 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: Don | Statement: [Fulgencio Yegros, title, Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Don
Context triple: [Fulgencio Yegros, title, Don]
  • A. Don
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • B. Don
    Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
  • C. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • D. Don
    The Don is a river in western France that flows through the Brittany region before joining the Vilaine.
  • E. Danny
    Danny is a masculine given name, often used as a diminutive of Daniel.
  • 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: Don
Triple: [Fulgencio Yegros, title, Don]
Generated description
Don is a Spanish honorific title historically used to denote respect and high social status, often associated with nobility or distinguished gentlemen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Don
Target entity description: Don is a Spanish honorific title historically used to denote respect and high social status, often associated with nobility or distinguished gentlemen.
  • A. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • B. Don
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • C. Don
    Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
  • D. Don
    The Don is a river in western France that flows through the Brittany region before joining the Vilaine.
  • E. Danny
    Danny is a fictional character from the musical "Proud Mary."
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e1749bc8190a8b9cbcb27288a5b completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01f931408190828d87567cecaceb completed May 9, 2026, 9:44 a.m.
NEDg Description generation batch_69ff034de0508190aea8068e9c3d04d3 completed May 9, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69ff03c0ebc081908b1a132256e9d004 completed May 9, 2026, 9:52 a.m.
Created at: April 10, 2026, 3:17 a.m.