Triple

T27786863
Position Surface form Disambiguated ID Type / Status
Subject slopes of Mount Makalu E700983 entity
Predicate poseRisk P62537 FINISHED
Object falls 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: falls | Statement: [slopes of Mount Makalu, poseRisk, falls]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: poseRisk
Context triple: [slopes of Mount Makalu, poseRisk, falls]
  • A. riskElement chosen
    Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
  • B. AlexanderRisk
    Indicates a relationship where Alexander is exposed to, associated with, or responsible for a particular risk or potential adverse outcome.
  • C. riskType
    Indicates the category or nature of risk associated with an entity, event, or relationship.
  • D. riskTaken
    Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
  • E. riskTheme
    Indicates a relationship where an entity is associated with, categorized under, or characterized by a particular type or theme of risk.
  • 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_69ef6a50d8088190acbf3dfbb06d8091 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f637d2e5e08190bc1708336a4fbfc5 completed May 2, 2026, 5:43 p.m.
PD Predicate disambiguation batch_69f6318ae6f08190b3f85f9201046a15 completed May 2, 2026, 5:16 p.m.
Created at: April 27, 2026, 5:25 p.m.