Triple

T13848746
Position Surface form Disambiguated ID Type / Status
Subject Clémence Poésy E332878 entity
Predicate notableWork P4 FINISHED
Object 127 Hours E62150 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: 127 Hours | Statement: [Clémence Poésy, notableWork, 127 Hours]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 127 Hours
Context triple: [Clémence Poésy, notableWork, 127 Hours]
  • A. 127 Hours chosen
    127 Hours is a biographical survival drama film directed by Danny Boyle that tells the true story of mountaineer Aron Ralston’s entrapment in a Utah canyon.
  • B. The Impossible
    The Impossible is a 2012 disaster drama film that recounts the true story of a family's struggle to survive and reunite in the aftermath of the 2004 Indian Ocean tsunami.
  • C. Argo
    Argo is the legendary ship of Greek mythology that carried Jason and the Argonauts on their quest for the Golden Fleece.
  • D. Argo
    Argo is a 2012 political thriller film directed by Ben Affleck that dramatizes a covert operation to rescue American hostages from Iran during the 1979–1981 crisis.
  • E. Argo
    Argo is a popular open-source suite of Kubernetes-native tools for running and managing container-native workflows, applications, and continuous delivery pipelines.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02b2a9788190b164760adec64ef6 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0f35ba48190b8b071679251233f completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.