Triple
T32751153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banyu Urip field |
E837498
|
entity |
| Predicate | fieldNameLanguage |
P151534
|
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: [Banyu Urip field, fieldNameLanguage, Indonesian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldNameLanguage Context triple: [Banyu Urip field, fieldNameLanguage, Indonesian]
-
A.
languageOfField
Indicates that a particular language is used as the primary or relevant language within a specified field, domain, or area of activity.
-
B.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
C.
labelNameLanguage
chosen
Indicates the language in which a given label or name is expressed.
-
D.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
E.
languageName
Indicates the specific name assigned to a language in the relationship.
- 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_69f34937f97c8190b7f84bea045df3ae |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 1:12 a.m.