Triple
T34694152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navajo-Apachean |
E890978
|
entity |
| Predicate | includesLanguageVarietyType |
P205527
|
FINISHED |
| Object | tonal 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: tonal languages | Statement: [Navajo-Apachean, includesLanguageVarietyType, tonal languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesLanguageVarietyType Context triple: [Navajo-Apachean, includesLanguageVarietyType, tonal languages]
-
A.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
B.
hasLinguisticVariationType
Indicates that one linguistic form is related to another by a specific type of variation, such as dialectal, orthographic, morphological, or phonological difference.
-
C.
denotesLanguageVariety
Indicates that one entity specifies the particular variety, dialect, or form of language used or associated with another entity.
-
D.
includesLanguage
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
-
E.
languageVariants
Indicates that one language form is a variant or alternative version of another language.
- F. None of above. chosen
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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 2:05 a.m.