Triple
T21652333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vale do São Francisco |
E534368
|
entity |
| Predicate | hasAgriculturalModel |
P144877
|
FINISHED |
| Object | irrigated perimeters |
—
|
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: irrigated perimeters | Statement: [Vale do São Francisco, hasAgriculturalModel, irrigated perimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgriculturalModel Context triple: [Vale do São Francisco, hasAgriculturalModel, irrigated perimeters]
-
A.
hasAgriculturalType
Indicates that an entity is associated with or classified by a specific type or category of agriculture.
-
B.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
C.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
D.
hasAgriculturalAssociation
Indicates that there exists a formal or recognized connection between an entity and an agricultural organization, group, or activity.
-
E.
representsAgriculture
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation to another entity.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:36 p.m.