Triple

T5540215
Position Surface form Disambiguated ID Type / Status
Subject Sapir–Whorf hypothesis E145269 entity
Predicate hasExampleDomain P1259 FINISHED
Object Eskimo–Aleut words for snow (popular but contested example) 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: Eskimo–Aleut words for snow (popular but contested example) | Statement: [Sapir–Whorf hypothesis, hasExampleDomain, Eskimo–Aleut words for snow (popular but contested example)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasExampleDomain
Context triple: [Sapir–Whorf hypothesis, hasExampleDomain, Eskimo–Aleut words for snow (popular but contested example)]
  • A. hasExample chosen
    Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
  • B. exampleDomain
    Indicates a general or illustrative relationship used as a placeholder within a specific conceptual or application domain.
  • C. hasNonExample
    Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
  • D. inputDomain
    Indicates that a function, process, or system accepts inputs belonging to a specified domain or set of allowable values.
  • E. typicalDomain
    Indicates that one entity is the characteristic or most common domain, context, or area of application in which another entity typically occurs or is used.
  • 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_69c008fa64888190adae56c8f9ea4031 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01fb487648190948493fe96cec0ff completed March 22, 2026, 4:58 p.m.
PD Predicate disambiguation batch_69c01b0c50e48190a1b03ecd20ca440b completed March 22, 2026, 4:38 p.m.
Created at: March 22, 2026, 3:35 p.m.