Triple
T599877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wollongong |
E11468
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object | Port Kembla |
E81321
|
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: Port Kembla | Statement: [Wollongong, hasSuburb, Port Kembla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Port Kembla Context triple: [Wollongong, hasSuburb, Port Kembla]
-
A.
Port Kembla
chosen
Port Kembla is a major deep-water seaport and industrial hub on the New South Wales south coast of Australia, known for its steelworks and bulk cargo facilities.
-
B.
Wyong
Wyong is a town and administrative centre on the Central Coast of New South Wales, Australia.
-
C.
Port Stephens
Port Stephens is a large natural harbour and popular coastal tourist destination on the New South Wales mid-north coast of Australia, known for its beaches, marine life, and water-based recreation.
-
D.
Kingscliff
Kingscliff is a coastal town in northeastern New South Wales, Australia, known for its beaches, surf breaks, and relaxed holiday atmosphere.
-
E.
Port Macquarie
Port Macquarie is a coastal town in New South Wales, Australia, known for its beaches, koala population, and role as a popular holiday destination.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d78c0f08190b83ad89062ccb0b9 |
completed | March 1, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a6373fbf388190afb01fcfd67f03bf |
completed | March 3, 2026, 1:19 a.m. |
Created at: March 1, 2026, 7:35 p.m.