Triple
T18816043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonnarua |
E460136
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Wonnawa |
—
|
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: Wonnawa | Statement: [Wonnarua, hasAlternativeName, Wonnawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonnawa Context triple: [Wonnarua, hasAlternativeName, Wonnawa]
-
A.
Wonnar
chosen
Wonnar is an alternative name for the Wonnarua, an Aboriginal Australian people traditionally associated with the Hunter Valley region of New South Wales.
-
B.
Wotho
Wotho is a small inhabited island in the Marshall Islands that serves as the main settlement and administrative center of Wotho Atoll.
-
C.
Wiluna
Wiluna is a remote outback town in Western Australia known historically as a gold mining center and as a gateway to desert tracks such as the Canning Stock Route.
-
D.
Wanhatti
Wanhatti is a village in Suriname known as a Maroon settlement located within the country’s eastern Marowijne District.
-
E.
Wondo
Wondo is the nickname of Chris Wondolowski, a prolific American soccer forward best known for his record-breaking goal-scoring career in Major League Soccer with the San Jose Earthquakes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a3e092e081908fc310c70f646e79 |
completed | April 20, 2026, 3:56 a.m. |
Created at: April 10, 2026, 11:55 a.m.