Triple
T5615550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayanic languages |
E147467
|
entity |
| Predicate | arealFeatureOf |
P24620
|
FINISHED |
| Object | Bornean 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: Bornean languages | Statement: [Kayanic languages, arealFeatureOf, Bornean languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arealFeatureOf Context triple: [Kayanic languages, arealFeatureOf, Bornean languages]
-
A.
arealFeature
Indicates a relationship where something is characterized as a spatial or geographic feature occupying an area on a surface or map.
-
B.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
C.
refersToGeographicFeature
Indicates that one entity makes reference to, denotes, or is associated with a specific geographic feature such as a landform, body of water, or other physical location.
-
D.
politicalFeature
Indicates that an entity possesses a political characteristic, attribute, or aspect relevant to governance, power structures, or public policy.
-
E.
arealRelation
chosen
Indicates a spatial relationship between areas, such as overlap, containment, adjacency, or relative positioning between two regions.
- 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_69c00905d4588190bd967842bbcf2219 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c021d8d600819097df4e265e262d90 |
completed | March 22, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.