Triple

T11733565
Position Surface form Disambiguated ID Type / Status
Subject Steve Pugh E278964 entity
Predicate workedOn P3 FINISHED
Object Hotwire E942300 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: Hotwire | Statement: [Steve Pugh, workedOn, Hotwire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hotwire
Context triple: [Steve Pugh, workedOn, Hotwire]
  • A. Hotwire
    Hotwire is an online travel agency known for offering discounted rates on hotels, flights, and rental cars through opaque and standard booking options.
  • B. Hotwire
    Hotwire is a science fiction comic series known for its gritty, cyberpunk-inspired storytelling and striking artwork.
  • C. Hotwire: Requiem for the Dead
    Hotwire: Requiem for the Dead is a science fiction comic series following a tough, technologically savvy exorcist who polices restless spirits in a dystopian future city.
  • D. Hotwire: Deep Cut chosen
    Hotwire: Deep Cut is a comic book series illustrated by Steve Pugh that blends science fiction and action in a gritty, futuristic setting.
  • E. The Hot Spot
    The Hot Spot is a 1990 neo-noir thriller film directed by Dennis Hopper and starring Don Johnson, Virginia Madsen, and Jennifer Connelly, known for its sultry atmosphere and crime-driven plot in a small Texas town.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4daa7f48190896fc7653e9dd70b completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0199f595081908c10ecd7dd3900e7 completed April 28, 2026, 2:21 a.m.
Created at: April 8, 2026, 9:41 p.m.