Triple
T33378001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebsdorfergrund |
E854687
|
entity |
| Predicate | hasRuralEconomyFocus |
P116329
|
FINISHED |
| Object | agriculture |
—
|
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: agriculture | Statement: [Ebsdorfergrund, hasRuralEconomyFocus, agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralEconomyFocus Context triple: [Ebsdorfergrund, hasRuralEconomyFocus, agriculture]
-
A.
hasRuralEconomySector
Indicates that an entity participates in, contains, or is associated with an economic sector based on rural activities or rural development.
-
B.
hasRuralFocus
chosen
Indicates that the subject is oriented toward, concerned with, or primarily serving rural areas or rural-related issues.
-
C.
hasEconomicFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in economic matters, activities, or impacts.
-
D.
agriculturalDependence
Indicates that one entity relies on another for agricultural resources, production, or support.
-
E.
hasAgriculturalCommunities
Indicates that certain groups or settlements engage in organized farming and related agricultural activities within a given area or context.
- 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_69f3496ca10c8190908640d18fa00832 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: May 1, 2026, 1:35 a.m.