Triple

T14277930
Position Surface form Disambiguated ID Type / Status
Subject Terry George E353961 entity
Predicate notableWork P4 FINISHED
Object Hotel Rwanda E373094 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: Hotel Rwanda | Statement: [Terry George, notableWork, Hotel Rwanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hotel Rwanda
Context triple: [Terry George, notableWork, Hotel Rwanda]
  • A. Hotel Rwanda chosen
    Hotel Rwanda is a 2004 historical drama film depicting the true story of a hotel manager who shelters Tutsi refugees during the Rwandan genocide.
  • B. Busi in Hotel Rwanda
    Busi in *Hotel Rwanda* is a supporting character who works as a hotel receptionist and represents the ordinary Rwandans caught in the midst of the 1994 genocide.
  • C. God Sleeps in Rwanda
    God Sleeps in Rwanda is a documentary film that explores the lives and resilience of Rwandan women in the aftermath of the 1994 genocide.
  • D. Rwanda Rising
    Rwanda Rising is a documentary film by Kimberlee Acquaro that explores Rwanda’s post-genocide recovery and efforts at national reconciliation and development.
  • E. The Killing Fields
    The Killing Fields is a 1984 historical drama film about the Cambodian genocide under the Khmer Rouge, focusing on the harrowing experiences of a journalist and his interpreter.
  • 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_69d8278d25148190abf1a8c8f5f533ad completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6585270c8190a717127b2f5dab3b completed April 14, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd326f62b4819084b1e984678991ae completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:10 a.m.