Triple
T7131322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wüllen |
E166193
|
entity |
| Predicate | hasRuralUrbanClassification |
P60791
|
FINISHED |
| Object | rural area |
—
|
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: rural area | Statement: [Wüllen, hasRuralUrbanClassification, rural area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralUrbanClassification Context triple: [Wüllen, hasRuralUrbanClassification, rural area]
-
A.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
B.
isRuralOrUrban
chosen
Indicates whether an entity is classified as being in a rural area or an urban area.
-
C.
hasUrbanRuralGmina
Indicates that an entity is associated with a specific urban-rural gmina (a mixed urban and rural municipal administrative unit).
-
D.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
E.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
- 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66f15b88190bc1fb0f0a8af16a6 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:44 p.m.