Triple
T18525977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alun-Alun Bandung |
E452718
|
entity |
| Predicate | localLanguageUsed |
P115774
|
FINISHED |
| Object | Sundanese |
—
|
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: Sundanese | Statement: [Alun-Alun Bandung, localLanguageUsed, Sundanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localLanguageUsed Context triple: [Alun-Alun Bandung, localLanguageUsed, Sundanese]
-
A.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
D.
languageUsedInLocality
chosen
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
E.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53392618c8190b44de46b80ee6a6d |
completed | April 19, 2026, 7:57 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:37 a.m.