Triple

T6688691
Position Surface form Disambiguated ID Type / Status
Subject Budong-Budong language E152166 entity
Predicate hasSyntaxFeature P5192 FINISHED
Object prepositional language 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: prepositional language | Statement: [Budong-Budong language, hasSyntaxFeature, prepositional language]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSyntaxFeature
Context triple: [Budong-Budong language, hasSyntaxFeature, prepositional language]
  • A. hasFeature
    Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
  • B. languageFeature chosen
    Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
  • C. hasFeatureCode
    Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
  • D. supportsFeature
    Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
  • E. hasSupported
    Indicates that one entity has provided assistance, endorsement, or backing to another entity, either materially, emotionally, or through advocacy.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6cd0fa5188190a23281cb09d98139 completed March 27, 2026, 6:31 p.m.
PD Predicate disambiguation batch_69c6ad0d3c1081908dadff7a6a054123 completed March 27, 2026, 4:15 p.m.
Created at: March 27, 2026, 2:04 p.m.