Triple

T984971
Position Surface form Disambiguated ID Type / Status
Subject Alpha Dog E21257 entity
Predicate cinematographyBy P1953 FINISHED
Object Robert Fraisse E34846 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: Robert Fraisse | Statement: [Alpha Dog, cinematographyBy, Robert Fraisse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Fraisse
Context triple: [Alpha Dog, cinematographyBy, Robert Fraisse]
  • A. Robert Fraisse chosen
    Robert Fraisse is a French cinematographer known for his visually striking work on international films, including major war dramas and action features.
  • B. Philippe Erlanger
    Philippe Erlanger was a French historian and cultural administrator best known for initiating and organizing the creation of the Cannes Film Festival.
  • C. Frédéric Boissonnas
    Frédéric Boissonnas was a pioneering Swiss photographer renowned for his early 20th-century landscape and travel photography, particularly his influential work documenting Greece and its mountains.
  • D. Michel Macary
    Michel Macary is a French architect best known for co-designing major public venues, including the iconic Stade de France in Paris.
  • E. Victor Laloux
    Victor Laloux was a prominent French architect of the late 19th and early 20th centuries, best known for his grand Beaux-Arts railway stations and public buildings in Paris.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4959fe48190a78bd811cbc888ab completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae02f0424481909c533774f0169ca7 completed March 8, 2026, 11:14 p.m.
Created at: March 1, 2026, 7:41 p.m.