Triple

T20618457
Position Surface form Disambiguated ID Type / Status
Subject Jamnik E506629 entity
Predicate hasRelationshipWith P2830 FINISHED
Object Professor Burris 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: Professor Burris | Statement: [Jamnik, hasRelationshipWith, Professor Burris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Professor Burris
Context triple: [Jamnik, hasRelationshipWith, Professor Burris]
  • A. Professor Burris chosen
    Professor Burris is the skeptical psychology professor and narrator of B.F. Skinner’s utopian novel "Walden Two," through whose perspective the experimental community is explored and critiqued.
  • B. Professor LeBlanc
    Professor LeBlanc is a recurring comedic character from the classic American radio and television series "The Jack Benny Program."
  • C. Professor Birch
    Professor Birch is the resident Pokémon Professor of the Hoenn region, known for his fieldwork-based research on Pokémon habitats and distribution.
  • D. Professor Berg
    Professor Berg is the father of Michael Berg, a central character in Bernhard Schlink’s novel *The Reader*.
  • E. Professor Thorton
    Professor Thorton is a Marvel Comics scientist associated with the Weapon Plus program, known for his role in creating and experimenting on super-soldiers like Wolverine.
  • 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_69e6abdf9d7c8190969247a4ae55b781 completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:41 a.m.