Triple

T7730578
Position Surface form Disambiguated ID Type / Status
Subject Manda–Pengo subgroup E175238 entity
Predicate degreeOfMutualIntelligibility P7448 FINISHED
Object high among member 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: high among member languages | Statement: [Manda–Pengo subgroup, degreeOfMutualIntelligibility, high among member languages]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: degreeOfMutualIntelligibility
Context triple: [Manda–Pengo subgroup, degreeOfMutualIntelligibility, high among member languages]
  • A. areMutuallyIntelligibleToSomeDegree chosen
    Indicates that two or more languages or communication systems can be at least partially understood by each other’s users without prior learning or translation.
  • B. lessMutuallyIntelligibleThan
    Indicates that the level of mutual intelligibility between one pair of languages (or language varieties) is lower than that between another pair.
  • C. hasCommonLoanwordsFrom
    Indicates that two languages share loanwords that originate from the same source language.
  • D. shareLanguageInfluence
    Indicates that two entities affect or shape each other’s language use, development, or characteristics through mutual or shared influence.
  • E. linguisticallyRelatedTo
    Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7074eca4c8190bd51fd1b450729e8 completed March 27, 2026, 10:40 p.m.
PD Predicate disambiguation batch_69c7016a6cf88190b53bf4b958f0f302 completed March 27, 2026, 10:15 p.m.
Created at: March 27, 2026, 4:06 p.m.