Triple

T20007999
Position Surface form Disambiguated ID Type / Status
Subject Salva E494508 entity
Predicate aliasOf P39 FINISHED
Object The Professor 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: The Professor | Statement: [Salva, aliasOf, The Professor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Professor
Context triple: [Salva, aliasOf, The Professor]
  • A. The Professor chosen
    The Professor is the mastermind strategist and enigmatic leader who orchestrates the meticulously planned heists in the Spanish series "Money Heist."
  • B. The Professor
    The Professor is the nickname of Ghanaian former professional boxer Azumah Nelson, a legendary world champion widely regarded as one of Africa’s greatest fighters.
  • C. The Professor
    The Professor is Charlotte Brontë’s first written novel, a realist work about an Englishman who becomes a teacher in Belgium, published posthumously under her pen name Currer Bell.
  • D. The Professor
    The Professor is the nickname of Igor Larionov, a highly intelligent and visionary Russian ice hockey center renowned for his playmaking and strategic understanding of the game.
  • E. The Professor
    The Professor is a mysterious, high-ranking U.S. intelligence official who orchestrates the covert operation at the center of Alfred Hitchcock’s film "North by Northwest."
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a7500481908b69f74e479f88c8 completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:33 p.m.