Triple
T6548947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese occupation security forces in Indonesia |
E151079
|
entity |
| Predicate | usedLocalLanguage |
P18209
|
FINISHED |
| Object | Malay |
—
|
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: Malay | Statement: [Japanese occupation security forces in Indonesia, usedLocalLanguage, Malay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLocalLanguage Context triple: [Japanese occupation security forces in Indonesia, usedLocalLanguage, Malay]
-
A.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
B.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
D.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
-
E.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
- 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_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. |
Created at: March 27, 2026, 1:51 p.m.