Triple

T24583328
Position Surface form Disambiguated ID Type / Status
Subject Sirionó language E608310 entity
Predicate hasPersonMarkersOnVerbs P50348 FINISHED
Object yes 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: yes | Statement: [Sirionó language, hasPersonMarkersOnVerbs, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPersonMarkersOnVerbs
Context triple: [Sirionó language, hasPersonMarkersOnVerbs, yes]
  • A. hasPersonMarkingOnVerb chosen
    Indicates that the verb carries explicit grammatical marking that identifies or agrees with the person (e.g., first, second, third person) of its subject or argument.
  • B. hasTenseAspectMoodMarkers
    Indicates that an expression includes explicit markers specifying its tense, aspect, and/or mood.
  • C. hasVerbAspect
    Indicates that a verb or verbal expression is associated with a particular grammatical aspect (such as perfective, imperfective, or progressive) describing the temporal structure of the action or state.
  • D. hasCaseMarking
    Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
  • E. hasVerbalMorphology
    Indicates that one linguistic element exhibits verbal inflectional properties or patterns in relation to another.
  • 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_69e2c4ce89248190ad99e18f0638dfbb completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a984577881908c855f5e05756909 completed April 30, 2026, 12:59 a.m.
PD Predicate disambiguation batch_69f2a6c1f07081908edf0b521767e79b completed April 30, 2026, 12:48 a.m.
Created at: April 18, 2026, 2:29 a.m.