Triple
T12460314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Te Awamutu |
E297772
|
entity |
| Predicate | hasHinterlandType |
P85002
|
FINISHED |
| Object | dairy farming hinterland |
—
|
LITERAL 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: dairy farming hinterland | Statement: [Te Awamutu, hasHinterlandType, dairy farming hinterland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHinterlandType Context triple: [Te Awamutu, hasHinterlandType, dairy farming hinterland]
-
A.
hasRuralHinterland
Indicates that a place or urban area is associated with and served by a surrounding rural region that supports it economically, socially, or functionally.
-
B.
hasLandComponent
Indicates that something includes, consists of, or is associated with a land-based part or portion as one of its components.
-
C.
hasRuralLandscapeType
chosen
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
D.
hasTypeOfSubdivision
Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
-
E.
hasNearbyTownType
Indicates that one entity has, in its vicinity, a town of a specified type or classification.
- F. None of above.
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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.