Triple

T7740899
Position Surface form Disambiguated ID Type / Status
Subject Miguel Herrán E175506 entity
Predicate familyName P18 FINISHED
Object Herrán
Herrán is the surname of Spanish actor Miguel Herrán, known for his roles in the series "Money Heist" and the film "A Cambio de Nada."
 E686007 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: Herrán | Statement: [Miguel Herrán, familyName, Herrán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Herrán
Context triple: [Miguel Herrán, familyName, Herrán]
  • A. Ayamonte
    Ayamonte is a Spanish border town in the province of Huelva, Andalusia, situated at the mouth of the Guadiana River opposite Portugal.
  • B. San Javier
    San Javier is a municipality in Spain’s Region of Murcia, known for hosting the Spanish Air and Space Force’s main officer training academy and its nearby coastal and lagoon areas on the Mar Menor.
  • C. San Javier
    San Javier is a Chilean town known for its agricultural activity and wine production in the Maule Region.
  • D. Lebrija
    Lebrija is a historic town and municipality in southern Spain’s Andalusia region, known for its agricultural economy and traditional flamenco culture.
  • E. Girón
    Girón is a historic colonial-era town and municipality in northeastern Colombia, renowned for its preserved whitewashed architecture and cobblestone streets.
  • 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: Herrán
Triple: [Miguel Herrán, familyName, Herrán]
Generated description
Herrán is the surname of Spanish actor Miguel Herrán, known for his roles in the series "Money Heist" and the film "A Cambio de Nada."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Herrán
Target entity description: Herrán is the surname of Spanish actor Miguel Herrán, known for his roles in the series "Money Heist" and the film "A Cambio de Nada."
  • A. Ayamonte
    Ayamonte is a Spanish border town in the province of Huelva, Andalusia, situated at the mouth of the Guadiana River opposite Portugal.
  • B. San Javier
    San Javier is a municipality in Spain’s Region of Murcia, known for hosting the Spanish Air and Space Force’s main officer training academy and its nearby coastal and lagoon areas on the Mar Menor.
  • C. San Javier
    San Javier is a Chilean town known for its agricultural activity and wine production in the Maule Region.
  • D. Lebrija
    Lebrija is a historic town and municipality in southern Spain’s Andalusia region, known for its agricultural economy and traditional flamenco culture.
  • E. Girón
    Girón is a historic colonial-era town and municipality in northeastern Colombia, renowned for its preserved whitewashed architecture and cobblestone streets.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7035df9348190ad3f3d845207bf4d completed March 27, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be4178408190850c284aab895442 completed March 29, 2026, 5:53 a.m.
NEDg Description generation batch_69c8bf30e83c819084f1c04b686d81a7 completed March 29, 2026, 5:57 a.m.
NED2 Entity disambiguation (via description) batch_69c8bfbb67888190a92de6c6c9562da4 completed March 29, 2026, 5:59 a.m.
Created at: March 27, 2026, 4:07 p.m.