Triple
T879701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid North Coast |
E18998
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Taree |
E52795
|
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: Taree | Statement: [Mid North Coast, hasPart, Taree]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taree Context triple: [Mid North Coast, hasPart, Taree]
-
A.
Taree
chosen
Taree is a regional town in New South Wales, Australia, situated on the Manning River and serving as a commercial and service hub for the surrounding agricultural and coastal communities.
-
B.
Tongaat
Tongaat is a town in KwaZulu-Natal, South Africa, known for its significant Indian community and sugar industry.
-
C.
Fitiuta
Fitiuta is a small village on the island of Taʻū in American Samoa, known for its traditional Samoan culture and coastal setting.
-
D.
Yamba
Yamba is a coastal town in northern New South Wales, Australia, known for its beaches, fishing, and laid-back holiday atmosphere.
-
E.
Murrurundi
Murrurundi is a small rural town in New South Wales, Australia, known for its scenic setting in the Upper Hunter region and its historic buildings.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acc9d5f4819087afbb75b6ac3dbf |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4bfe2ce081908c358689ec2c58e6 |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:39 p.m.