Triple

T3859892
Position Surface form Disambiguated ID Type / Status
Subject A View to a Kill E90108 entity
Predicate villain P4675 FINISHED
Object Max Zorin E398003 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: Max Zorin | Statement: [A View to a Kill, villain, Max Zorin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Zorin
Context triple: [A View to a Kill, villain, Max Zorin]
  • A. Max Zorin chosen
    Max Zorin is the main villain in the James Bond film "A View to a Kill," a ruthless industrialist plotting to destroy Silicon Valley for financial gain.
  • B. Victor Argo
    Victor Argo was an American character actor known for his frequent collaborations with directors like Martin Scorsese and Abel Ferrara, often portraying tough, streetwise New Yorkers in crime and drama films.
  • C. Felix Krull
    Felix Krull is the charming, quick-witted con artist and social climber who narrates Thomas Mann’s picaresque novel "The Confessions of Felix Krull."
  • D. Arnim Zola
    Arnim Zola is a Marvel Comics supervillain and mad scientist known for transferring his consciousness into robotic bodies and serving as a key genetic engineer for Hydra.
  • E. Cyrus Voris
    Cyrus Voris is an American screenwriter and producer best known for co-writing films like "Bulletproof Monk" and co-creating the television series "Sleeper Cell."
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec1ff39c8190b83a88abd840a0e3 completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5283ccf68819086c6349ceb71f099 completed March 14, 2026, 9:19 a.m.
Created at: March 9, 2026, 3:19 p.m.