Triple
T7063420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther Burbank |
E164280
|
entity |
| Predicate | numberOfPlantVarietiesDeveloped |
P49018
|
FINISHED |
| Object | over 800 |
—
|
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: over 800 | Statement: [Luther Burbank, numberOfPlantVarietiesDeveloped, over 800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlantVarietiesDeveloped Context triple: [Luther Burbank, numberOfPlantVarietiesDeveloped, over 800]
-
A.
numberOfPrimaryVarieties
Indicates the count of distinct primary varieties associated with a given entity.
-
B.
numberOfPlants
Indicates the total count of plants associated with a given entity or context.
-
C.
hasApproximateNumberOfVarieties
chosen
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
D.
numberOfCrops
Indicates the quantity or count of crops associated with a given entity or context.
-
E.
exportCultivar
Indicates the action of sending a plant cultivar from one place or organization to another for use, trade, or distribution.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:38 p.m.