Triple

T14253813
Position Surface form Disambiguated ID Type / Status
Subject Dimensions in Time E353334 entity
Predicate featuresCharacter P626 FINISHED
Object K9 E71121 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: K9 | Statement: [Dimensions in Time, featuresCharacter, K9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: K9
Context triple: [Dimensions in Time, featuresCharacter, K9]
  • A. K-9
    K-9 is a 1989 American buddy cop comedy film starring James Belushi as a detective partnered with a police dog to take down a drug dealer.
  • B. K-9 chosen
    K-9 is a robotic dog from the Doctor Who universe, known as a loyal, intelligent companion equipped with advanced technology and weaponry.
  • C. K9K
    K9K is a Canadian postal code prefix assigned to part of the city of Peterborough in Ontario.
  • D. K-99
    K-99 is a north–south state highway running through eastern Kansas, connecting several small towns and rural areas.
  • E. K9FIN Moukari
    K9FIN Moukari is a Finnish-modified version of the South Korean K9 Thunder self-propelled howitzer, tailored to meet Finland’s specific operational and environmental requirements.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6297f38c819090d7c7fd8bfa2e9e completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55008a5c8190b005a12df7ef2f75 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:09 a.m.