Triple
T19869557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wieluń County |
E477475
|
entity |
| Predicate | hasMixtureOfUrbanAndRuralCommunities |
P24917
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Wieluń County, hasMixtureOfUrbanAndRuralCommunities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMixtureOfUrbanAndRuralCommunities Context triple: [Wieluń County, hasMixtureOfUrbanAndRuralCommunities, true]
-
A.
hasUrbanRuralMix
chosen
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
B.
urbanRuralSplit
Indicates a division or distinction between urban and rural areas, conditions, or populations.
-
C.
hasSuburbanAreas
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
-
D.
isRuralSuburbanCommunity
Indicates that a community is characterized by a mix of rural and suburban features, typically lying between fully urbanized and sparsely populated rural areas.
-
E.
hasRuralCommunes
Indicates that an entity possesses, includes, or is associated with one or more rural communes.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a2cc8481908d134b0b5cf79d06 |
completed | April 20, 2026, 4:47 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.