Triple

T11773994
Position Surface form Disambiguated ID Type / Status
Subject Bear in the Big Blue House E279969 entity
Predicate mainCharacter P1183 FINISHED
Object Bear E241117 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: Bear | Statement: [Bear in the Big Blue House, mainCharacter, Bear]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bear
Context triple: [Bear in the Big Blue House, mainCharacter, Bear]
  • A. Bear
    "Bear" is the NATO reporting name for the Tupolev Tu-95, a long-range, turboprop-powered strategic bomber and maritime patrol aircraft developed by the Soviet Union.
  • B. bear chosen
    A bear is a large, typically omnivorous mammal known for its powerful build, thick fur, and presence in diverse habitats across the Northern Hemisphere and parts of the Southern Hemisphere.
  • C. Beary
    Beary is a Dravidian language spoken primarily by the Beary Muslim community in the coastal districts of Karnataka, India.
  • D. Bruiser the Bear
    Bruiser the Bear is the costumed bear mascot who represents Baylor University’s athletic teams and school spirit.
  • E. Badger
    Badger is a fictional character appearing in the work "The Return of Ulysses."
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a55dfa088190a59b35d0247225e3 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0909969e481908d836f912b5af5bf completed April 28, 2026, 10:48 a.m.
Created at: April 8, 2026, 9:41 p.m.