Triple
T15654399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oakey |
E376392
|
entity |
| Predicate | electoralDistrictFederal |
P1566
|
FINISHED |
| Object | Groom |
E1103659
|
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: Groom | Statement: [Oakey, electoralDistrictFederal, Groom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Groom Context triple: [Oakey, electoralDistrictFederal, Groom]
-
A.
Groom
Groom is a surname most notably associated with American novelist Winston Groom, the author of "Forrest Gump."
-
B.
Groom
chosen
Groom is an Australian federal electoral division in Queensland, centered on the city of Toowoomba and its surrounding rural areas.
-
C.
Batchelor
Batchelor is the surname of G. K. Batchelor, a prominent Australian applied mathematician and fluid dynamicist.
-
D.
Batchelor
Batchelor is a small town in Australia's Northern Territory that serves as a gateway to Litchfield National Park and nearby natural attractions.
-
E.
Hussey
Hussey is an English surname borne by various notable figures in fields such as religion, politics, and the arts.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef089948190902ec22f4d7bc932 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67994fbc819090f2da267888e8fb |
completed | May 9, 2026, 4:58 p.m. |
Created at: April 10, 2026, 4:15 a.m.