Triple
T20157823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheat Belt |
E491619
|
entity |
| Predicate | hasFarmStructure |
P72098
|
FINISHED |
| Object | large family farms |
—
|
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: large family farms | Statement: [Wheat Belt, hasFarmStructure, large family farms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFarmStructure Context triple: [Wheat Belt, hasFarmStructure, large family farms]
-
A.
hasFarm
Indicates that one entity owns, operates, or is responsible for a farm associated with another entity.
-
B.
farmingStructure
chosen
Indicates that one entity is a structure or facility used for farming-related activities in relation to another entity.
-
C.
hasNotableFarm
Indicates that an entity possesses or is associated with a farm that is considered notable or significant in some recognized way.
-
D.
hasRanch
Indicates that one entity owns, operates, or is associated with a ranch.
-
E.
hasPermanentStructures
Indicates that one entity possesses or contains long-lasting, fixed physical structures associated with it.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.