Triple
T24738674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kari’ña |
E618488
|
entity |
| Predicate | languageFamilyOfLanguage |
P35117
|
FINISHED |
| Object | Kari’ña language |
—
|
NE NERFINISHED |
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: Kari’ña language | Statement: [Kari’ña, languageFamilyOfLanguage, Kari’ña language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageFamilyOfLanguage Context triple: [Kari’ña, languageFamilyOfLanguage, Kari’ña language]
-
A.
languageFamilyOf
chosen
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
-
B.
languageFamily
Indicates that two or more languages belong to the same genealogical language family or linguistic lineage.
-
C.
languageFamilyAssociated
Indicates that there is an association or connection between a language and a particular language family.
-
D.
languageFamilyAssociation
Indicates an association where one entity belongs to, is classified under, or is related to a particular language family.
-
E.
languageOfFamily
Indicates the language or languages commonly used or associated with a particular family.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 4:04 a.m.