Triple

T8033092
Position Surface form Disambiguated ID Type / Status
Subject Logan E187033 entity
Predicate characterFeatured P12208 FINISHED
Object Wolverine E119393 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: Wolverine | Statement: [Logan, characterFeatured, Wolverine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolverine
Context triple: [Logan, characterFeatured, Wolverine]
  • A. Wolverine
    Wolverine is a higher-speed Amtrak passenger train service that operates multiple daily routes between Chicago, Detroit, and Pontiac in the Midwestern United States.
  • B. Wolverine chosen
    Wolverine is a popular Marvel Comics mutant superhero known for his retractable adamantium claws, accelerated healing factor, and membership in the X-Men.
  • C. Wolverine
    Wolverine is a fierce, small but powerful mammal known for its strength, tenacity, and association with toughness in sports and popular culture.
  • D. Wolverine Wildcat
    Wolverine Wildcat is a classic wooden roller coaster located at the Michigan’s Adventure amusement park in Muskegon, Michigan.
  • E. Magneto
    Magneto is a powerful Marvel Comics supervillain and occasional antihero, known as a mutant with magnetic abilities and a complex ideological rivalry with the X-Men.
  • 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_69ca82ae2d1081909dbfee42b41db419 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ef3e6848190913c4b1bef506aae completed March 31, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56ede1ac8190afd8a050e9a25851 completed March 31, 2026, 11:21 p.m.
Created at: March 30, 2026, 5:22 p.m.