Triple

T12138444
Position Surface form Disambiguated ID Type / Status
Subject Oko languages E289120 entity
Predicate degreeOfRelatedness P87413 FINISHED
Object closely related 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: closely related | Statement: [Oko languages, degreeOfRelatedness, closely related]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: degreeOfRelatedness
Context triple: [Oko languages, degreeOfRelatedness, closely related]
  • A. relationshipToRelative
    Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
  • B. relationshipToHumans
    Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
  • C. moreDistantlyRelatedTo
    Indicates that one entity is related to another by a more distant or indirect relationship compared to some closer reference relationship.
  • D. basisOfRelationship
    Indicates that one entity serves as the foundational reason, cause, or justification for the relationship that exists between two or more entities.
  • E. moreCloselyRelatedTo chosen
    Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference entity.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91841615c819097f20a7447a1b8f4 completed April 10, 2026, 3:33 p.m.
PD Predicate disambiguation batch_69d91508f8008190b3a90ec0bf0953ca completed April 10, 2026, 3:19 p.m.
Created at: April 8, 2026, 9:49 p.m.