Triple
T20926204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awabakal language |
E515350
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Awaba |
—
|
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: Awaba | Statement: [Awabakal language, alternativeName, Awaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Awaba Context triple: [Awabakal language, alternativeName, Awaba]
-
A.
Awaba
chosen
Awaba is an Aboriginal name historically used for Lake Macquarie, a large coastal lake in New South Wales, Australia.
-
B.
Abeïbara
Abeïbara is a small rural commune and village located in the remote desert area of northeastern Mali.
-
C.
Awaji
Awaji is a city located on Awaji Island in Japan, known for its scenic coastal landscapes, agriculture, and role as a gateway between Honshu and Shikoku.
-
D.
Abae
Abae was an ancient town in Phocis, Greece, best known for its important oracle of Apollo and its role in various Greek historical and religious events.
-
E.
Abiko
Abiko is a city in Chiba Prefecture, Japan, known for its residential character and location along the JR Joban Line northeast of central Tokyo.
- 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_69e0b4fb431c8190b9d40e6a72f0cc87 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f65200b08190ac208204a20f5a6a |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 12:49 p.m.