Triple

T17961650
Position Surface form Disambiguated ID Type / Status
Subject Dr. Kananga E449097 entity
Predicate franchise P1500 FINISHED
Object James Bond 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: James Bond | Statement: [Dr. Kananga, franchise, James Bond]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: James Bond
Context triple: [Dr. Kananga, franchise, James Bond]
  • A. James Bond chosen
    James Bond is a fictional British secret agent, code-named 007, known for his espionage missions, suave demeanor, and presence in a long-running series of novels and films.
  • B. Jimmy Bond
    Jimmy Bond is an American jazz double bassist known for his session work in the 1950s and 1960s with prominent artists such as Chet Baker and Nina Simone.
  • C. John Bond
    John Bond is a musician best known as a former member of the American rock band Story of the Year.
  • D. Guy Fleming
    Guy Fleming was a prominent American naturalist and conservationist known for his key role in preserving the Torrey Pines area in California.
  • E. Jack Bond
    Jack Bond is a British film and television director known for his work on music videos and collaborations with prominent artists.
  • 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b132cc10819088526a0b4b098d69 completed April 19, 2026, 10:40 a.m.
Created at: April 10, 2026, 10:22 a.m.