Triple

T5685910
Position Surface form Disambiguated ID Type / Status
Subject de Sucre E125312 entity
Predicate orthographicForm P2203 FINISHED
Object "de Sucre" E125312 NE FINISHED

How this triple was built (2 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 Sucre" | Statement: [de Sucre, orthographicForm, "de Sucre"]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: "de Sucre"
Context triple: [de Sucre, orthographicForm, "de Sucre"]
  • A. de Sucre chosen
    De Sucre is the surname of Antonio José de Sucre, a prominent Venezuelan independence leader and close ally of Simón Bolívar.
  • B. Dulcedo
    Dulcedo is a Latin term meaning "sweetness" or "delight," often used in Christian liturgical and devotional texts to express spiritual consolation and joy.
  • C. Sopó
    Sopó is a small municipality in the department of Cundinamarca, Colombia, known for its scenic Andean landscapes and dairy production.
  • D. Supía
    Supía is a municipality in the Caldas Department of Colombia, known historically for gold mining and its indigenous Emberá Chamí heritage.
  • E. Surquillo
    Surquillo is a densely populated urban district of Lima, Peru, known for its residential neighborhoods, markets, and proximity to the upscale area of Miraflores.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023ba52b48190b94f8a3ecff61eb4 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a40b3808190bc57fde5990ac04e completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.