Triple
T26121704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archdiocese of Bielsko-Żywiec |
E658987
|
entity |
| Predicate | hasMetropolitanCountry |
P46526
|
FINISHED |
| Object | Poland |
—
|
NE NERFINISHED |
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: Poland | Statement: [Archdiocese of Bielsko-Żywiec, hasMetropolitanCountry, Poland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetropolitanCountry Context triple: [Archdiocese of Bielsko-Żywiec, hasMetropolitanCountry, Poland]
-
A.
hasMetropolitan
Indicates that an entity is associated with, served by, or located within a specific metropolitan area.
-
B.
metropolitanSeeCountry
chosen
Indicates that a metropolitan area is associated with, located in, or belongs to a particular country.
-
C.
hasMetropolitanAreaType
Indicates that an entity is associated with a specific type or classification of metropolitan area (e.g., urban, suburban, metropolitan region category).
-
D.
isMetropolitanFor
Indicates that one entity serves as the primary metropolitan center or urban hub for another entity (such as a region, area, or service).
-
E.
hasMetropolitanCityCode
Indicates that an entity is associated with a specific metropolitan city identified by a standardized code.
- 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_69ee5bc2b2948190b458ad3f580af779 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 26, 2026, 8:09 p.m.