Triple

T16826399
Position Surface form Disambiguated ID Type / Status
Subject Attahiru Jega E409028 entity
Predicate workLocation P7 FINISHED
Object Kano E13198 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: Kano | Statement: [Attahiru Jega, workLocation, Kano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kano
Context triple: [Attahiru Jega, workLocation, Kano]
  • A. 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.
  • B. Kano
    Kano is a consumer electronics and education-focused technology company known for creating modular, learn-to-code kits and devices such as the Stem Player.
  • C. Kano chosen
    Kano is a major commercial and industrial city in northern Nigeria and one of the country’s oldest urban centers.
  • D. Sokoto
    Sokoto is a historic city in northwestern Nigeria that served as the capital of the Sokoto Caliphate and remains an important cultural and Islamic scholarly center.
  • E. Dutse
    Dutse is a city in northern Nigeria that serves as the administrative and economic center of Jigawa State.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b31404c88190a3b2802842ca77eb completed April 18, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b29e48f881908489bd77a9caec97 completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.