Triple

T5101966
Position Surface form Disambiguated ID Type / Status
Subject The Professor E114999 entity
Predicate alsoKnownAs P39 FINISHED
Object El Profesor E114999 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: El Profesor | Statement: [The Professor, alsoKnownAs, El Profesor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Profesor
Context triple: [The Professor, alsoKnownAs, El Profesor]
  • A. The Teacher
    The Teacher is the enigmatic and manipulative leader of the secretive religious sect in "The Da Vinci Code," commanding intense loyalty from followers like Silas.
  • B. The Professor chosen
    The Professor is the mastermind strategist and enigmatic leader who orchestrates the meticulously planned heists in the Spanish series "Money Heist."
  • C. El Maestro
    El Maestro is the legendary Argentine racing driver Juan Manuel Fangio, widely regarded as one of the greatest Formula One drivers in history.
  • D. The Tutor
    The Tutor is a satirical play by Bertolt Brecht that critiques bourgeois education and social hypocrisy through the misadventures of an opportunistic schoolteacher.
  • E. A Teacher
    A Teacher is a 2013 drama film and later television miniseries that explores the illicit relationship between a high school teacher and her student.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7584ed408190a6d1086588f24faa completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec36d231481908da4d2df53bd6507 completed March 21, 2026, 4:12 p.m.
Created at: March 20, 2026, 1:41 p.m.