Triple

T35882671
Position Surface form Disambiguated ID Type / Status
Subject Baining fire dance E1037553 entity
Predicate riskAspect P62537 FINISHED
Object direct contact with flames 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: direct contact with flames | Statement: [Baining fire dance, riskAspect, direct contact with flames]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: riskAspect
Context triple: [Baining fire dance, riskAspect, direct contact with flames]
  • A. riskElement chosen
    Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
  • B. riskType
    Indicates the category or nature of risk associated with an entity, event, or relationship.
  • C. riskFeature
    Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
  • D. riskDomain
    Indicates that something belongs to, is associated with, or falls under a particular area or category of risk.
  • E. riskGroup
    Indicates that an entity belongs to a category of individuals or items that share an elevated level of risk relative to others.
  • 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_69f76e1f4d748190bb55594d8441d70e completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa3883d48190b05e3d2da7a017ae completed May 3, 2026, 8:04 p.m.
PD Predicate disambiguation batch_69f7a8d435288190b30b1991fb003121 completed May 3, 2026, 7:58 p.m.
Created at: May 3, 2026, 4:06 p.m.