Triple
T4815554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tea Gardens |
E107178
|
entity |
| Predicate | distanceFrom |
P1299
|
FINISHED |
| Object | Sydney, New South Wales |
E8462
|
NE 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: Sydney, New South Wales | Statement: [Tea Gardens, distanceFrom, Sydney, New South Wales]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sydney, New South Wales Context triple: [Tea Gardens, distanceFrom, Sydney, New South Wales]
-
A.
Newcastle, New South Wales
Newcastle, New South Wales is a coastal Australian city known for its busy port, beaches, and historic industrial and coal-mining heritage.
-
B.
Sydney
chosen
Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
-
C.
Sydney
Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
-
D.
Wollongong
Wollongong is a coastal city in Australia known for its heavy industry, port facilities, and popular surf beaches along the Illawarra region.
-
E.
Brisbane
Brisbane is a small city in northern San Mateo County, California, located just south of San Francisco on the lower slopes of San Bruno Mountain.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c8230888190a676695e51cb3ea4 |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fa2f3e0819084ca792c1b08e3b9 |
completed | March 21, 2026, 10:14 a.m. |
Created at: March 20, 2026, 1:23 p.m.