Triple
T6202375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawthorn campus |
E138664
|
entity |
| Predicate | suburb |
P47577
|
FINISHED |
| Object | Hawthorn |
E135216
|
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: Hawthorn | Statement: [Hawthorn campus, suburb, Hawthorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hawthorn Context triple: [Hawthorn campus, suburb, Hawthorn]
-
A.
Hawthorn
chosen
Hawthorn is an inner suburb of Melbourne, Australia, known for its historic architecture, leafy streets, and proximity to major educational institutions.
-
B.
Hawthorn
Hawthorn is a village in the Taff-Ely area of Rhondda Cynon Taf, Wales.
-
C.
Waratah
Waratah is a suburban railway station in Newcastle, New South Wales, serving the local community on the regional rail network.
-
D.
Woodberry
Woodberry is a residential suburb located within the Maitland local government area in the Hunter Region of New South Wales, Australia.
-
E.
R and W Hawthorn
R and W Hawthorn was a 19th-century British engineering firm best known for manufacturing steam locomotives and marine engines.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626a32908190a3332008aee2e4a9 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f3bad2c8190b0ad0f2def3af9f7 |
completed | March 23, 2026, 4:50 p.m. |
Created at: March 22, 2026, 4:20 p.m.