Triple
T35159322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ord River region |
E1015216
|
entity |
| Predicate | hasLanguageRegionFor |
P145951
|
FINISHED |
| Object | Miriwoong language |
—
|
NE NERFINISHED |
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: Miriwoong language | Statement: [Ord River region, hasLanguageRegionFor, Miriwoong language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageRegionFor Context triple: [Ord River region, hasLanguageRegionFor, Miriwoong language]
-
A.
hasLanguageRegionContext
chosen
Indicates that something is associated with or situated within a specific linguistic or language-region context.
-
B.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
C.
subjectLanguageRegion
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
-
D.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
E.
operatorLanguageRegion
Indicates the geographic region or locale in which an operator’s language is used or applicable.
- 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_69f76ddb3a708190b521ba2970b17178 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff79e7206c8190a809b5f2a6261378 |
completed | May 9, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69ff798356b881908645074fb3a96517 |
completed | May 9, 2026, 6:14 p.m. |
Created at: May 3, 2026, 4:02 p.m.