Triple
T7365657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buronga |
E169862
|
entity |
| Predicate | associatedRegion |
P285
|
FINISHED |
| Object | Mallee |
E175845
|
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: Mallee | Statement: [Buronga, associatedRegion, Mallee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mallee Context triple: [Buronga, associatedRegion, Mallee]
-
A.
Mallee region
chosen
The Mallee region is a semi-arid agricultural and rural area in northwestern Victoria, Australia, known for its distinctive mallee eucalypt vegetation and grain farming.
-
B.
Kikuyu
Kikuyu is a major Bantu language spoken primarily by the Kikuyu people of central Kenya.
-
C.
Coolabah
Coolabah is a small rural town in western New South Wales, Australia, known for its remote outback setting and role as a service stop along regional transport routes.
-
D.
Acacias
Acacias is a Madrid Metro station serving the central Arganzuela district and providing access to nearby residential and commercial areas.
-
E.
Acacias
Acacias is a neighborhood located within the Benito Juárez borough of Mexico City, known for its residential character and urban amenities.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f163038481909dedbffb4ae7f860 |
completed | March 27, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802b90cc081908b15e61921d15b92 |
completed | March 28, 2026, 4:32 p.m. |
Created at: March 27, 2026, 3:06 p.m.