Triple

T6077268
Position Surface form Disambiguated ID Type / Status
Subject University of Dschang E135430 entity
Predicate locatedIn P40 FINISHED
Object Dschang E567551 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: Dschang | Statement: [University of Dschang, locatedIn, Dschang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dschang
Context triple: [University of Dschang, locatedIn, Dschang]
  • A. Dschang chosen
    Dschang is a city in western Cameroon known as an important educational and cultural center, home to the University of Dschang and a mild highland climate.
  • B. Garki
    Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
  • C. Mambasa
    Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
  • D. Njaba
    Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
  • E. Chindau
    Chindau is a Bantu language spoken primarily by the Ndau people in parts of Mozambique and Zimbabwe.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0576ef2c88190b0ec62e9f041d176 completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1252a178c81909a3d689ad748fb5e completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:11 p.m.