Triple
T27507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida |
E549
|
entity |
| Predicate | majorCrop |
P1897
|
FINISHED |
| Object | oranges |
—
|
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: oranges | Statement: [Florida, majorCrop, oranges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorCrop Context triple: [Florida, majorCrop, oranges]
-
A.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
B.
plantHeight
Indicates the measured vertical size or growth extent of a plant from its base to its top.
-
C.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
D.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
majorIsland
Indicates that an island is the primary or most significant island within a specified geographic or political context.
- F. None of above. chosen
Provenance (4 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a247798a348190bb943d38300ae3ef |
completed | Feb. 28, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69a24658749881909117b007ec3d8633 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a24778b73c81908e9f2eb8cdbcef73 |
completed | Feb. 28, 2026, 1:40 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.