Triple

T4439253
Position Surface form Disambiguated ID Type / Status
Subject Príncipe E95728 entity
Predicate regionalLanguage P237 FINISHED
Object Angolar E94969 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: Angolar | Statement: [Príncipe, regionalLanguage, Angolar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angolar
Context triple: [Príncipe, regionalLanguage, Angolar]
  • A. Angolar chosen
    Angolar is a Portuguese-based creole language spoken primarily by the Angolar community on the island of São Tomé in São Tomé and Príncipe.
  • B. Anglona
    Anglona is a historical and geographical subregion in northern Sardinia, Italy, known for its rural landscapes, medieval villages, and traditional Sardinian culture.
  • C. Agno
    Agno is a small Swiss town in the canton of Ticino, known for its lakeside location, regional airport, and proximity to Lugano.
  • D. Estyn
    Estyn is the education and training inspectorate for Wales, responsible for evaluating the quality and standards of schools, colleges, and other learning providers.
  • E. Angangueo
    Angangueo is a historic mining town in central Mexico best known as a gateway to the Monarch Butterfly Biosphere Reserve.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355aaa9288190b95d875d343d6ee5 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6137b97748190b8ebecaf590baad3 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:31 p.m.