Triple

T20623444
Position Surface form Disambiguated ID Type / Status
Subject Dig Up Her Bones E506757 entity
Predicate hasBside P15273 FINISHED
Object Bruiser 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: Bruiser | Statement: [Dig Up Her Bones, hasBside, Bruiser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bruiser
Context triple: [Dig Up Her Bones, hasBside, Bruiser]
  • A. Bruiser
    Bruiser is the costumed mascot character for the Saskatchewan-based professional lacrosse team, the Saskatoon Rush.
  • B. Bruiser chosen
    Bruiser is a 2000 psychological horror-thriller film directed by George A. Romero about a man who, after mysteriously losing his face, embarks on a vengeful rampage against those who have wronged him.
  • C. Bruiser the Bulldog
    Bruiser the Bulldog is the costumed canine mascot representing Adrian College at its athletic events and campus activities.
  • D. Bruiser the Bear
    Bruiser the Bear is the costumed bear mascot who represents Baylor University’s athletic teams and school spirit.
  • E. Intimidator
    Intimidator is a high-speed steel roller coaster at Carowinds themed after NASCAR legend Dale Earnhardt, known for its tall drops and intense airtime.
  • 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe3177c8190ad1b2ca8b1e0a560 completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:42 a.m.