Triple

T20688905
Position Surface form Disambiguated ID Type / Status
Subject Mortal Kombat 11 E508496 entity
Predicate hasCharacter P2308 FINISHED
Object Kano 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: Kano | Statement: [Mortal Kombat 11, hasCharacter, Kano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kano
Context triple: [Mortal Kombat 11, hasCharacter, Kano]
  • A. 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.
  • B. Kano
    Kano is a major commercial and industrial city in northern Nigeria and one of the country’s oldest urban centers.
  • C. Kano chosen
    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. 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.
  • 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_69e0b4c1ed408190b72dd26b1e33f8a1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6c10b7b808190bdb8b08e53168fb8 completed April 21, 2026, 12:12 a.m.
Created at: April 16, 2026, 11:56 a.m.