Triple

T16529497
Position Surface form Disambiguated ID Type / Status
Subject Traps: A Novel E401525 entity
Predicate hasTitle P38 FINISHED
Object Traps E85912 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: Traps | Statement: [Traps: A Novel, hasTitle, Traps]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Traps
Context triple: [Traps: A Novel, hasTitle, Traps]
  • A. Traps chosen
    "Traps" is a novel by MacKenzie Scott (formerly MacKenzie Bezos), known for its interwoven narratives about four women whose lives collide over a tense four-day period.
  • B. Traps
    "Traps" is a song by the British indie rock band Bloc Party, released as a single showcasing their energetic, guitar-driven style.
  • C. The Trap
    "The Trap" is a horror novel by Tabitha King that delves into psychological terror and the darker sides of human relationships in a small-town setting.
  • D. The Trap
    The Trap is a 1966 British adventure drama film set in the Canadian wilderness, starring Rita Tushingham and Oliver Reed.
  • E. Trampas
    Trampas is a recurring antagonist in Owen Wister’s Western novel *The Virginian*, known for his rivalry with the title character and embodiment of lawless frontier values.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed625208190a68b879266b05b3f completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00608efd0c81908e64419bd74eb285 completed May 10, 2026, 10:40 a.m.
Created at: April 10, 2026, 5:14 a.m.