Triple
T7056285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciboney language |
E164098
|
entity |
| Predicate | GlottologStatus |
P28208
|
FINISHED |
| Object | unclassified or unattested |
—
|
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: unclassified or unattested | Statement: [Ciboney language, GlottologStatus, unclassified or unattested]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GlottologStatus Context triple: [Ciboney language, GlottologStatus, unclassified or unattested]
-
A.
glottologStatus
chosen
Indicates the classification or status of a language or dialect as defined in the Glottolog database.
-
B.
glottocode
Indicates the standardized Glottolog code that uniquely identifies the language or dialect associated with an entity.
-
C.
hasGlottologName
Indicates that an entity is associated with a specific name as recorded in the Glottolog linguistic database.
-
D.
glottoCategory
Indicates the linguistic classification or type (such as language family, subgroup, or category) to which a language or dialect is assigned.
-
E.
hasEthnologueEntry
Indicates that there exists an entry for the subject in the Ethnologue language reference resource.
- 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_69c68861678881909961ddf4d779f750 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:38 p.m.