Triple

T122981
Position Surface form Disambiguated ID Type / Status
Subject Wear OS E2486 entity
Predicate supportsLanguage P2177 FINISHED
Object multiple languages 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: multiple languages | Statement: [Wear OS, supportsLanguage, multiple languages]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: supportsLanguage
Context triple: [Wear OS, supportsLanguage, multiple languages]
  • A. includesLanguage chosen
    Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
  • B. recognizedLanguage
    Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
  • C. isLanguageOf
    Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
  • D. isWorldLanguage
    Indicates that a language is widely used across multiple countries or regions and serves as a common means of communication beyond its original native community.
  • E. hasSignificantLanguage
    Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
  • 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a2573b4e7481909ee09d2899f8a74b completed Feb. 28, 2026, 2:47 a.m.
PD Predicate disambiguation batch_69a2564928208190966a619680a0d6e2 completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:24 a.m.