Triple

T8498745
Position Surface form Disambiguated ID Type / Status
Subject Patrick Crowley E201161 entity
Predicate notableWork P4 FINISHED
Object Green Zone E212665 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: Green Zone | Statement: [Patrick Crowley, notableWork, Green Zone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Zone
Context triple: [Patrick Crowley, notableWork, Green Zone]
  • A. Green Zone, Baghdad chosen
    The Green Zone in Baghdad is a heavily fortified district that serves as the center of Iraq’s government and many foreign diplomatic missions.
  • B. Ground Zero
    Ground Zero is a survival horror video game level or scenario known for its intense atmosphere and challenging gameplay.
  • C. Ground Zero
    Ground Zero is a thriller novel by F. Paul Wilson featuring his recurring character Repairman Jack as he investigates a deadly conspiracy linked to the aftermath of the 9/11 attacks.
  • D. Ground Zero
    Ground Zero is a 1987 Australian political thriller film about a cameraman uncovering a government cover-up surrounding British nuclear tests in the outback.
  • E. Black Hawk Down
    Black Hawk Down is a 2001 war film directed by Ridley Scott that dramatizes the 1993 U.S. military raid in Mogadishu, Somalia.
  • 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_69ca831ee390819095fae73400bbfafc completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5984d7481908c41c57bef9cf254 completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e0aa7788190abd7bb259966bc44 completed April 2, 2026, 11:07 a.m.
Created at: March 30, 2026, 6:14 p.m.