Triple

T24798948
Position Surface form Disambiguated ID Type / Status
Subject Nguna–Tongoa languages E620466 entity
Predicate haveMorphologyType P1250 FINISHED
Object moderately analytic 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: moderately analytic | Statement: [Nguna–Tongoa languages, haveMorphologyType, moderately analytic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: haveMorphologyType
Context triple: [Nguna–Tongoa languages, haveMorphologyType, moderately analytic]
  • A. hasMorphologicalType chosen
    Indicates that an entity possesses or is classified by a particular morphological type or structural form.
  • B. hasMorphologicalState
    Indicates that an entity possesses or is characterized by a particular morphological condition, form, or structural state.
  • C. hasMorphosyntax
    Indicates a relationship where an entity is associated with, characterized by, or analyzed in terms of its morphological and syntactic structure.
  • D. hasMorphosyntacticBasis
    Indicates that one linguistic element’s form or syntactic behavior is grounded in, derived from, or systematically determined by another element’s morphosyntactic properties.
  • E. hasMorphologicalMix
    Indicates that an entity exhibits a combination of different morphological types or structures within a single form or system.
  • 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_69e2fabe77c8819085f7ce6486248139 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f412a8d7d081909a4b961eadefd30e completed May 1, 2026, 2:40 a.m.
PD Predicate disambiguation batch_69f40ef612c88190ab2f3f08d4a92018 completed May 1, 2026, 2:24 a.m.
Created at: April 18, 2026, 4:49 a.m.