Triple

T9801608
Position Surface form Disambiguated ID Type / Status
Subject Wilson Bethel E237849 entity
Predicate portrayedIn P626 FINISHED
Object Generation Kill E726101 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: Generation Kill | Statement: [Wilson Bethel, portrayedIn, Generation Kill]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Generation Kill
Context triple: [Wilson Bethel, portrayedIn, Generation Kill]
  • A. Generation Kill chosen
    Generation Kill is a nonfiction book by Evan Wright and an HBO miniseries adaptation that chronicle the experiences of a U.S. Marine reconnaissance battalion during the 2003 invasion of Iraq.
  • B. The Killing Floor
    The Killing Floor is a 1984 American television drama film about African American stockyard workers in 1910s Chicago and their struggle to unionize amid racial tensions.
  • C. Shoot to Kill
    Shoot to Kill is a 1988 American thriller film about an FBI agent and a mountain guide tracking a murderous criminal through the wilderness.
  • D. The Big Kill
    The Big Kill is a hardboiled crime novel featuring private investigator Mike Hammer, written by American mystery author Mickey Spillane.
  • E. The Killing Ground
    The Killing Ground is a thriller novel by Jack Higgins featuring his recurring character Sean Dillon in a high-stakes tale of terrorism, kidnapping, and covert operations.
  • 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda62b41048190bcef70a7591830c6 completed April 1, 2026, 11:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc53c3dc819084a4d8b72164a172 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:29 p.m.