Triple

T11818120
Position Surface form Disambiguated ID Type / Status
Subject Memphis Mad Dogs E281054 entity
Predicate mascot P52 FINISHED
Object Mad Dog E763776 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: Mad Dog | Statement: [Memphis Mad Dogs, mascot, Mad Dog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mad Dog
Context triple: [Memphis Mad Dogs, mascot, Mad Dog]
  • A. Mad Dog chosen
    Mad Dog is the vicious outlaw gunslinger and primary antagonist in the 1885 segment of the film "Back to the Future Part III."
  • B. Mad Dogs
    Mad Dogs is a British dark comedy-drama television series about a group of middle-aged friends whose holiday in Spain spirals into crime and chaos.
  • C. Black Dogs
    "Black Dogs" is a 1992 novel by Ian McEwan that explores the aftermath of World War II and the clash between rationalism and spiritual belief through the story of a troubled marriage.
  • D. White Dog
    White Dog is a crime novel in the Jack Irish series by Australian author Peter Temple, featuring the Melbourne lawyer and debt-collector embroiled in a complex investigation.
  • E. White Dog
    White Dog is a 1982 American drama-horror film directed by Samuel Fuller that explores racism through the story of a dog trained to attack Black people.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5e760988190b50d13bba5ef5b43 completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f131cbf9708190ba8394fb3508b975 completed April 28, 2026, 10:16 p.m.
Created at: April 8, 2026, 9:42 p.m.