Triple
T2704966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manawatū-Whanganui Region |
E59320
|
entity |
| Predicate | containsLandscapeFeature |
P22129
|
FINISHED |
| Object | agricultural plains |
—
|
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: agricultural plains | Statement: [Manawatū-Whanganui Region, containsLandscapeFeature, agricultural plains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsLandscapeFeature Context triple: [Manawatū-Whanganui Region, containsLandscapeFeature, agricultural plains]
-
A.
hasLandscapeFeatures
chosen
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
B.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
C.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
D.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
E.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda518c58819096c8b67c0f754655 |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.