Triple
T17097990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chivi District |
E414898
|
entity |
| Predicate | hasAgriculturalChallenge |
P125911
|
FINISHED |
| Object | low and erratic rainfall |
—
|
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: low and erratic rainfall | Statement: [Chivi District, hasAgriculturalChallenge, low and erratic rainfall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgriculturalChallenge Context triple: [Chivi District, hasAgriculturalChallenge, low and erratic rainfall]
-
A.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
B.
agriculturalImpact
Indicates the effect that an action, condition, or entity has on agricultural systems, productivity, or practices.
-
C.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
D.
agriculturalImplication
Indicates a relationship where one factor, event, or condition has consequences, effects, or relevance specifically within an agricultural context.
-
E.
agriculturalDependence
Indicates that one entity relies on another for agricultural resources, production, or support.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbffafb08190baf9e0b4fdf1b404 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d67b14481909fcdbdeaa5c34785 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.