Triple

T20863406
Position Surface form Disambiguated ID Type / Status
Subject Pushover E513682 entity
Predicate hasTheme P261 FINISHED
Object fatal attraction 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: fatal attraction | Statement: [Pushover, hasTheme, fatal attraction]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: fatal attraction
Context triple: [Pushover, hasTheme, fatal attraction]
  • A. fatal attraction chosen
    Fatal attraction is an intense, obsessive romantic or sexual fixation that drives a person toward destructive, often violent behavior and tragic outcomes.
  • B. Fatal Attractions
    Fatal Attractions is a major 1993 X-Men crossover storyline in Marvel Comics, best known for Magneto ripping the adamantium from Wolverine’s skeleton and its lasting impact on the mutant universe.
  • C. Fatal Attraction
    Fatal Attraction is a 1987 psychological thriller film about a married man's affair that spirals into violent obsession, starring Michael Douglas and Glenn Close.
  • D. Foetal Attraction
    Foetal Attraction is a humorous, feminist novel by Australian author Kathy Lette that satirically explores pregnancy, relationships, and modern womanhood.
  • E. Entrange
    Entrange is a small commune in the Moselle department of northeastern France, situated near the borders with Luxembourg and Germany.
  • 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c45d2ec4819098abbb901b9fcd87 completed April 21, 2026, 12:27 a.m.
Created at: April 16, 2026, 12:44 p.m.