Triple

T9666988
Position Surface form Disambiguated ID Type / Status
Subject Duke City E233730 entity
Predicate hasRelatedNickname P11214 FINISHED
Object Burque E237330 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: Burque | Statement: [Duke City, hasRelatedNickname, Burque]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burque
Context triple: [Duke City, hasRelatedNickname, Burque]
  • A. Burque chosen
    Burque is a colloquial nickname commonly used to refer to the city of Albuquerque, New Mexico.
  • B. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • C. Herrera
    Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
  • D. Villacarlos
    Villacarlos is the former name of Es Castell, a coastal town on the island of Menorca in Spain known for its natural harbor and military history.
  • E. Tingo María
    Tingo María is a city in central Peru known as the gateway to the Amazon and for its surrounding rainforest landscapes and national park.
  • 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_69ca848d3b6c8190ae98ea554dea58df completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c3a63948190be3f48f87bdbccf1 completed April 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18a1c8b188190bcff470244b21640 completed April 4, 2026, 10:01 p.m.
Created at: March 30, 2026, 8:15 p.m.