Triple
T26595968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulau Meja |
E667490
|
entity |
| Predicate | languageUsedInLocalArea |
P115774
|
FINISHED |
| Object | Indonesian |
—
|
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: Indonesian | Statement: [Pulau Meja, languageUsedInLocalArea, Indonesian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedInLocalArea Context triple: [Pulau Meja, languageUsedInLocalArea, Indonesian]
-
A.
languageUsedInLocality
chosen
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
B.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
C.
languageOfSurroundingCountry
Indicates that a language is the primary or commonly used language in the country surrounding a given place or region.
-
D.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
E.
languageOfLocalOrganization
Indicates the language used or officially adopted by a local organization in its operations or communications.
- 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_69ee9cfc385081909ac9ae178030a06e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: April 27, 2026, 2:10 a.m.