Triple

T2438979
Position Surface form Disambiguated ID Type / Status
Subject Luis Almagro E53228 entity
Predicate familyName P18 FINISHED
Object Almagro
Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
 E270941 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: Almagro | Statement: [Luis Almagro, familyName, Almagro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Almagro
Context triple: [Luis Almagro, familyName, Almagro]
  • A. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • B. Ancud
    Ancud is a coastal city on northern Chiloé Island in southern Chile, known historically as a Spanish stronghold and for its maritime heritage and nearby natural landscapes.
  • C. Carabajal
    Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
  • D. Serón
    Serón is a small rural settlement located in the Río Hurtado area of northern Chile, known for its Andean landscapes and agricultural surroundings.
  • E. La Calera
    La Calera is a Colombian town and municipality in the Andean department of Cundinamarca, known for its mountainous landscapes and proximity to Bogotá.
  • 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: Almagro
Triple: [Luis Almagro, familyName, Almagro]
Generated description
Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Almagro
Target entity description: Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
  • A. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • B. Ancud
    Ancud is a coastal city on northern Chiloé Island in southern Chile, known historically as a Spanish stronghold and for its maritime heritage and nearby natural landscapes.
  • C. Carabajal
    Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
  • D. Serón
    Serón is a small rural settlement located in the Río Hurtado area of northern Chile, known for its Andean landscapes and agricultural surroundings.
  • E. La Calera
    La Calera is a Colombian town and municipality in the Andean department of Cundinamarca, known for its mountainous landscapes and proximity to Bogotá.
  • 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_69ab495b6dac8190ac82661aa1452222 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f62ad081909373134c5adf65d9 completed March 7, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69af178a0f0c81909f6629f3fed76e2c completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af1ba6e1408190ac021c1c1d1c3b2e completed March 9, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_69af1c53dbe481908f73e1fe8d61c32e completed March 9, 2026, 7:15 p.m.
Created at: March 6, 2026, 9:43 p.m.