Triple

T21968423
Position Surface form Disambiguated ID Type / Status
Subject BR-304 E542517 entity
Predicate connectsCity P4245 FINISHED
Object Assu NE NERFINISHED

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: Assu | Statement: [BR-304, connectsCity, Assu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Assu
Context triple: [BR-304, connectsCity, Assu]
  • A. Assu chosen
    Assu is a municipality in the Brazilian state of Rio Grande do Norte, known for its regional commerce and cultural traditions in the semi-arid Northeast.
  • B. Aasu
    Aasu is a small village located on the island of Tutuila in American Samoa.
  • C. Assi
    Assi is a prominent neighborhood in Varanasi, India, best known for the nearby Assi Ghat on the banks of the Ganges River.
  • D. Asen
    Asen was a medieval Bulgarian noble and co-leader, with his brother Peter, of the uprising that restored the Second Bulgarian Empire in the late 12th century.
  • E. Assas
    Assas is the commonly used short name for Université Paris 2 Panthéon-Assas, a prestigious French university renowned for its law and social sciences programs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47fab1081908dc74a6545dbb051 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1245c5d148190af2a06190ba32feb completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8:02 p.m.