Triple

T28933213
Position Surface form Disambiguated ID Type / Status
Subject North Atlantic Central Water E733842 entity
Predicate propertyDistribution P172383 FINISHED
Object horizontally extensive layer of nearly uniform properties 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: horizontally extensive layer of nearly uniform properties | Statement: [North Atlantic Central Water, propertyDistribution, horizontally extensive layer of nearly uniform properties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: propertyDistribution
Context triple: [North Atlantic Central Water, propertyDistribution, horizontally extensive layer of nearly uniform properties]
  • A. property
    Indicates that one entity possesses, is characterized by, or has an attribute or quality associated with another entity.
  • B. propertyDivisionWith
    Indicates a relationship in which two or more parties are involved in dividing or allocating ownership or rights to property between them.
  • C. propertyHeld
    Indicates that a particular property is possessed, owned, or controlled by a specified entity.
  • D. ownedProperty
    Indicates that one entity possesses legal ownership or control over another entity as property.
  • E. studiedProperty
    Indicates that an entity has examined, researched, or analyzed a particular property or attribute of another entity.
  • 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_69f05b0b49b08190b8994b339c7980f6 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f6abe15d5c81909ccf4ce37f78bc43 completed May 3, 2026, 1:58 a.m.
PD Predicate disambiguation batch_69f6aa1c555081908787dbf76147f180 completed May 3, 2026, 1:51 a.m.
PDg Predicate description generation batch_69f6aaf31a548190b2f792ff4b8c002a completed May 3, 2026, 1:54 a.m.
Created at: April 28, 2026, 8:30 a.m.