Triple

T36003961
Position Surface form Disambiguated ID Type / Status
Subject Macro-Gulf (proposed) E1041211 entity
Predicate includesLanguageCandidate P2177 FINISHED
Object Apalachee language E311169 NE 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: Apalachee language | Statement: [Macro-Gulf (proposed), includesLanguageCandidate, Apalachee language]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: includesLanguageCandidate
Context triple: [Macro-Gulf (proposed), includesLanguageCandidate, Apalachee language]
  • A. includesLanguage chosen
    Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
  • B. eligibleLanguage
    Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
  • C. includesLanguageCluster
    Indicates that one entity contains or encompasses a specific group or cluster of related languages as part of its composition or scope.
  • D. possibleLanguage
    Indicates that an entity could plausibly be expressed, interpreted, or communicated in a given language.
  • E. usesLanguageFor
    Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
  • F. None of above.

Provenance (4 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_69f76e2a02208190aedd1f9025a8b300 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_6a037c8d06cc8190ab6a5e18d9d2571e completed May 12, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38cb8965fc8190a369486aa71e9256 completed June 22, 2026, 5:43 a.m.
PD Predicate disambiguation batch_6a037a0895b48190acdd88dc10db7be7 completed May 12, 2026, 7:05 p.m.
Created at: May 3, 2026, 4:07 p.m.