Triple

T9568103
Position Surface form Disambiguated ID Type / Status
Subject The Virginian E230838 entity
Predicate characterPortrayed P1507 FINISHED
Object Trampas E806790 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: Trampas | Statement: [The Virginian, characterPortrayed, Trampas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trampas
Context triple: [The Virginian, characterPortrayed, Trampas]
  • A. Trampas chosen
    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.
  • B. The Trick
    The Trick is a British drama film in which George MacKay stars in a story inspired by the real-life "Climategate" email hacking scandal.
  • 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. Traps
    "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.
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9987cb0c8190af32a1193de54890 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d16149c7808190b476ec06e9780a03 completed April 4, 2026, 7:06 p.m.
Created at: March 30, 2026, 8:04 p.m.