Triple

T11607113
Position Surface form Disambiguated ID Type / Status
Subject Antonio Saca E275289 entity
Predicate familyName P18 FINISHED
Object Saca
Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
 E936434 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: Saca | Statement: [Antonio Saca, familyName, Saca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saca
Context triple: [Antonio Saca, familyName, Saca]
  • A. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • B. Toma
    Toma is a traditional semi-hard cow’s milk cheese from Italy’s Piedmont region, known for its mild, buttery flavor and smooth, elastic texture.
  • C. Sanz
    Sanz is a prominent Hasidic dynasty known for its strong emphasis on Torah scholarship, strict halachic observance, and influential rabbinic leadership originating in 19th-century Galicia.
  • D. Jocoaitique
    Jocoaitique is a small municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
  • E. Sakaar
    Sakaar is a chaotic, trash-covered planet ruled by the Grandmaster in the Marvel Cinematic Universe, known for its gladiatorial contests and bizarre cosmic detritus.
  • 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: Saca
Triple: [Antonio Saca, familyName, Saca]
Generated description
Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saca
Target entity description: Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
  • A. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • B. Toma
    Toma is a traditional semi-hard cow’s milk cheese from Italy’s Piedmont region, known for its mild, buttery flavor and smooth, elastic texture.
  • C. Sanz
    Sanz is a prominent Hasidic dynasty known for its strong emphasis on Torah scholarship, strict halachic observance, and influential rabbinic leadership originating in 19th-century Galicia.
  • D. Jocoaitique
    Jocoaitique is a small municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
  • E. Cáqueza
    Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d89551649c81908096ff392677442d completed April 10, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69e8a82381708190aa0e674603d5778a completed April 22, 2026, 10:51 a.m.
NEDg Description generation batch_69e8af9665648190b7732076aa129671 completed April 22, 2026, 11:23 a.m.
NED2 Entity disambiguation (via description) batch_69ee5b3a3720819095a4a87176e052cb completed April 26, 2026, 6:36 p.m.
Created at: April 8, 2026, 9:38 p.m.