Triple
T9432533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ostrów Mazowiecka County |
E227416
|
entity |
| Predicate | hasUrbanRuralStructure |
P40698
|
FINISHED |
| Object | urban gminas and rural gminas |
—
|
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: urban gminas and rural gminas | Statement: [Ostrów Mazowiecka County, hasUrbanRuralStructure, urban gminas and rural gminas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanRuralStructure Context triple: [Ostrów Mazowiecka County, hasUrbanRuralStructure, urban gminas and rural gminas]
-
A.
hasUrbanRuralMix
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
B.
urbanRuralSplit
chosen
Indicates a division or distinction between urban and rural areas, conditions, or populations.
-
C.
isRuralOrUrban
Indicates whether an entity is classified as being in a rural area or an urban area.
-
D.
hasUrbanRuralGmina
Indicates that an entity is associated with a specific urban-rural gmina (a mixed urban and rural municipal administrative unit).
-
E.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e61a114819081fc4a2ad39c96ba |
completed | April 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:49 p.m.