Triple

T1117621
Position Surface form Disambiguated ID Type / Status
Subject Rhône Glacier E11136 entity
Predicate climateChangeIndicator P25138 FINISHED
Object example of rapid glacial retreat 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: example of rapid glacial retreat | Statement: [Rhône Glacier, climateChangeIndicator, example of rapid glacial retreat]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: climateChangeIndicator
Context triple: [Rhône Glacier, climateChangeIndicator, example of rapid glacial retreat]
  • A. climateChangeEffect
    Indicates how climate change influences or alters a particular entity, condition, or process.
  • B. climate
    Indicates a relationship where environmental or atmospheric conditions influence, shape, or characterize something (such as a place, system, or process).
  • C. climaticChallenge
    Indicates a relationship where an entity faces, contributes to, or is affected by significant difficulties or stresses arising from climate or weather conditions.
  • D. hasClimate
    Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
  • E. climatologicalSignificance
    Indicates the degree to which something is important, influential, or relevant within the context of climate or long-term weather patterns.
  • F. None of above. chosen

Provenance (4 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_69a493252a648190ac48f8742474a5e8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bc4bc21881909dcfe628f59f3e8c completed March 1, 2026, 10:23 p.m.
PD Predicate disambiguation batch_69a4bb4562f48190831e959f5f309956 completed March 1, 2026, 10:18 p.m.
PDg Predicate description generation batch_69a4bc47fce48190825d3a877251f789 completed March 1, 2026, 10:23 p.m.
Created at: March 1, 2026, 7:43 p.m.