Triple
T1732912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Belt (U.S. region) |
E37852
|
entity |
| Predicate | historicallyDominantCrop |
P1897
|
FINISHED |
| Object | cotton |
—
|
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: cotton | Statement: [Black Belt (U.S. region), historicallyDominantCrop, cotton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicallyDominantCrop Context triple: [Black Belt (U.S. region), historicallyDominantCrop, cotton]
-
A.
majorCrop
chosen
Indicates that a particular crop is one of the primary or most important crops cultivated in a given area or context.
-
B.
widelyCultivatedIn
Indicates that something is grown extensively or on a large scale within a particular place or region.
-
C.
cultivatedFor
Indicates that one entity is intentionally grown, raised, or developed for the benefit, use, or purpose of another entity.
-
D.
crop
Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
-
E.
isMajorCommercialCultivar
Indicates that an entity is a widely grown and economically important cultivated variety used in commercial production.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab5c553e508190b0f511b05e07fa20 |
completed | March 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69aa61c25a648190892de94c997fb983 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.