Triple
T27382683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mińsk County |
E691276
|
entity |
| Predicate | hasMetropolitanAffiliation |
P5047
|
FINISHED |
| Object | Warsaw metropolitan area |
—
|
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: Warsaw metropolitan area | Statement: [Mińsk County, hasMetropolitanAffiliation, Warsaw metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetropolitanAffiliation Context triple: [Mińsk County, hasMetropolitanAffiliation, Warsaw metropolitan area]
-
A.
hasMetropolitan
chosen
Indicates that an entity is associated with, served by, or located within a specific metropolitan area.
-
B.
hasMetropolitanChapterAt
Indicates that an organization or body maintains a metropolitan-level chapter or branch located at a specified place.
-
C.
hasMetropolitanConnectionWith
Indicates that there is a significant relationship or linkage between two entities based on shared or interacting metropolitan areas, such as through infrastructure, services, or regional integration.
-
D.
hasMetropolitanRankOver
Indicates that one entity has a higher metropolitan rank or status than another entity.
-
E.
hasMetropolitanAreaType
Indicates that an entity is associated with a specific type or classification of metropolitan area (e.g., urban, suburban, metropolitan region category).
- 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_69ef52022538819081f873d0c84a6dd6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: April 27, 2026, 12:23 p.m.