Triple
T7261239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aru languages |
E159656
|
entity |
| Predicate | arealUnit |
P25535
|
FINISHED |
| Object | Eastern Indonesia linguistic area |
—
|
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: Eastern Indonesia linguistic area | Statement: [Aru languages, arealUnit, Eastern Indonesia linguistic area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arealUnit Context triple: [Aru languages, arealUnit, Eastern Indonesia linguistic area]
-
A.
areaUnit
Indicates the unit of measurement used to express an area value in a given context.
-
B.
arealFeature
Indicates a relationship where something is characterized as a spatial or geographic feature occupying an area on a surface or map.
-
C.
arealRegion
chosen
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb088dac8190b353f6ea3d686025 |
completed | March 27, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69c6e76876608190ac4652bc7153302e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:57 p.m.