Triple

T35199496
Position Surface form Disambiguated ID Type / Status
Subject Between a Rock and a Hard Place E1016357 entity
Predicate describesInjury P23450 FINISHED
Object traumatic arm entrapment LITERAL 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: traumatic arm entrapment | Statement: [Between a Rock and a Hard Place, describesInjury, traumatic arm entrapment]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: describesInjury
Context triple: [Between a Rock and a Hard Place, describesInjury, traumatic arm entrapment]
  • A. injuryType chosen
    Indicates the specific kind or category of injury associated with an entity or event.
  • B. causeOfInjury
    Indicates that one entity is the source or reason that another entity sustained an injury.
  • C. injuryStatus
    Indicates the condition or state of harm, damage, or physical injury affecting an entity.
  • D. hasPlaceOfInjury
    Indicates that an injury occurred at a specific place or location.
  • E. injuryPlotPoint
    Indicates that an event in the narrative involves a character being injured, serving as a significant plot development or turning point.
  • F. None of above.

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_69f76dde814c8190a71f60d514a424a4 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fd3a69f1e08190a11aed015bff0858 completed May 8, 2026, 1:20 a.m.
PD Predicate disambiguation batch_69fd39124180819080ca7911d3515d6d completed May 8, 2026, 1:14 a.m.
Created at: May 3, 2026, 4:02 p.m.