Triple

T11745194
Position Surface form Disambiguated ID Type / Status
Subject Bielefeld E279260 entity
Predicate hasTwinTown P919 FINISHED
Object Estelí E100316 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: Estelí | Statement: [Bielefeld, hasTwinTown, Estelí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Estelí
Context triple: [Bielefeld, hasTwinTown, Estelí]
  • A. Estelí chosen
    Estelí is a city in northern Nicaragua known for its tobacco production, cigar industry, and role as a commercial and cultural center in the region.
  • B. Chichigalpa
    Chichigalpa is a Nicaraguan town known for its sugarcane industry and as the home of the Flor de Caña rum distillery.
  • C. Juigalpa
    Juigalpa is a city in central Nicaragua that serves as the capital of the Chontales Department and a regional hub for agriculture and cattle ranching.
  • D. Matagalpa
    Matagalpa is a major city in north-central Nicaragua known for its coffee production, cool climate, and role as a regional commercial and educational hub.
  • E. Tibacuy
    Tibacuy is a small municipality and town in the Cundinamarca Department of central Colombia, known for its rural character and Andean landscapes.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f2a38c8190a682d8dae1ab9415 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019e4f0988190afe0b92f4c9d8073 completed April 28, 2026, 2:22 a.m.
Created at: April 8, 2026, 9:41 p.m.