Triple

T10934963
Position Surface form Disambiguated ID Type / Status
Subject Vègre E258307 entity
Predicate environmentalCategory P31092 FINISHED
Object river of France 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: river of France | Statement: [Vègre, environmentalCategory, river of France]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: environmentalCategory
Context triple: [Vègre, environmentalCategory, river of France]
  • A. environmentalFocus
    Indicates a relationship where an entity prioritizes or concentrates on environmental issues, impacts, or sustainability in its actions or policies.
  • B. environmentalIssue
    Indicates that something is a problem or concern related to the natural environment, such as harm, risk, or negative impact on ecosystems or resources.
  • C. environmentalMedium chosen
    Indicates the environmental context or medium (such as air, water, or soil) through which a substance, effect, or process occurs or is present.
  • D. environmentalSignificance
    Indicates the importance or impact that something has on the natural environment, such as its role in conservation, degradation, or ecological balance.
  • E. environmentAuthority
    Indicates that an entity has official regulatory or supervisory power over environmental matters affecting another entity or area.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770aee178819082c1671a37ff7d82 completed April 9, 2026, 9:26 a.m.
PD Predicate disambiguation batch_69d72e816a98819096d6c10dfb88a66a completed April 9, 2026, 4:43 a.m.
Created at: April 8, 2026, 9:23 p.m.