Triple

T5884803
Position Surface form Disambiguated ID Type / Status
Subject Life of Pi E130835 entity
Predicate author P4 FINISHED
Object Yann Martel E111061 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: Yann Martel | Statement: [Life of Pi, author, Yann Martel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yann Martel
Context triple: [Life of Pi, author, Yann Martel]
  • A. Yann Martel chosen
    Yann Martel is a Canadian author best known for his philosophical novel "Life of Pi," which achieved international acclaim and widespread popularity.
  • B. Markus Zusak
    Markus Zusak is an Australian novelist best known for his internationally acclaimed World War II–set novel "The Book Thief."
  • C. Paulo Coelho
    Paulo Coelho is a Brazilian novelist best known for his inspirational allegorical works such as "The Alchemist," which have achieved worldwide popularity and influence.
  • D. Vikas Swarup
    Vikas Swarup is an Indian diplomat and novelist best known for his debut novel "Q & A," which was adapted into the Oscar-winning film "Slumdog Millionaire."
  • E. Sandra Pullman
    Sandra Pullman is a determined, by-the-book detective who leads a team of retired officers investigating cold cases in the British television series "New Tricks."
  • 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_69c0085628dc8190b334c1b44c067efc completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0367743508190bae211e9ce8f9690 completed March 22, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b13839f48190b23f22d5317eb571 completed March 23, 2026, 3:19 a.m.
Created at: March 22, 2026, 3:57 p.m.