Triple
T24366432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Small Nambas area |
E614206
|
entity |
| Predicate | traditionalLanguageRegionOf |
P96310
|
FINISHED |
| Object | Small Nambas 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: Small Nambas language | Statement: [Small Nambas area, traditionalLanguageRegionOf, Small Nambas language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalLanguageRegionOf Context triple: [Small Nambas area, traditionalLanguageRegionOf, Small Nambas language]
-
A.
formerLanguageRegion
Indicates that a region previously used a particular language as significant or dominant, but no longer does so.
-
B.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
C.
hasTraditionalLanguageRegion
chosen
Indicates the geographic region traditionally associated with the use or origin of a particular language.
-
D.
motherTongueRegion
Indicates the geographic region where an entity’s native or primary language is predominantly spoken or originates.
-
E.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
- 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_69e2d7dfe7f08190b7a1f3a36483ab05 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2938809f081908abf33edb62ed7f8 |
completed | April 29, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:01 a.m.