Triple

T19053463
Position Surface form Disambiguated ID Type / Status
Subject Samara E466325 entity
Predicate roadNetworkLinkedTo P11435 FINISHED
Object Zaria city E65252 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: Zaria city | Statement: [Samara, roadNetworkLinkedTo, Zaria city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaria city
Context triple: [Samara, roadNetworkLinkedTo, Zaria city]
  • A. Zaria chosen
    Zaria is a historic city in northern Nigeria known as an important center of Hausa culture, Islamic scholarship, and trade.
  • B. Layyah city
    Layyah city is a growing urban center in Punjab, Pakistan, known for its agricultural economy and role as an administrative and commercial hub for the surrounding rural region.
  • C. Kano
    Kano is a long-running Mortal Kombat villain known as a ruthless mercenary and leader of the Black Dragon crime syndicate, often depicted with a cybernetic eye and expertise in knives and dirty fighting tactics.
  • D. Kano
    Kano is a British rapper and actor known as one of the pioneering figures of the UK grime scene.
  • E. Kano
    Kano is a major commercial and industrial city in northern Nigeria and one of the country’s oldest urban centers.
  • 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_69d8dd040fb881909af2a964f65ad208 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5dc03dfa08190924a1b8073364fa1 completed April 20, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05e6622bfc81908c90aaf8d3b039fa completed May 14, 2026, 3:12 p.m.
Created at: April 10, 2026, 12:03 p.m.