Triple
T5581696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apsua |
E146654
|
entity |
| Predicate | linguisticContext |
P27440
|
FINISHED |
| Object | Abkhaz language |
—
|
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: Abkhaz language | Statement: [Apsua, linguisticContext, Abkhaz language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticContext Context triple: [Apsua, linguisticContext, Abkhaz language]
-
A.
linguisticUsage
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
-
B.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
C.
linguisticSignificance
Indicates the degree to which something is important, influential, or meaningful within a particular language or linguistic system.
-
D.
sociolinguisticSituation
chosen
Indicates the social and cultural context in which language is used, including factors like participants, setting, norms, and power relations that shape linguistic behavior.
-
E.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0208147a48190b2cdb42b9c9814a3 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:37 p.m.