Triple
T6549209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indonesian nationalism |
E151086
|
entity |
| Predicate | promotedLanguage |
P72315
|
FINISHED |
| Object | Indonesian language |
—
|
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 language | Statement: [Indonesian nationalism, promotedLanguage, Indonesian language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: promotedLanguage Context triple: [Indonesian nationalism, promotedLanguage, Indonesian language]
-
A.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
B.
focusesOnLanguage
Indicates that an entity’s primary attention, activity, or content is directed toward language as its main subject or concern.
-
C.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
D.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
E.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
- F. None of above. chosen
Provenance (4 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6ce0538f48190abf3160681901c17 |
completed | March 27, 2026, 6:35 p.m. |
Created at: March 27, 2026, 1:51 p.m.