Triple
T26007414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaalimaa |
E646795
|
entity |
| Predicate | hasNearbyMunicipalCenter |
P34698
|
FINISHED |
| Object | Virolahti municipal centre |
—
|
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: Virolahti municipal centre | Statement: [Vaalimaa, hasNearbyMunicipalCenter, Virolahti municipal centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMunicipalCenter Context triple: [Vaalimaa, hasNearbyMunicipalCenter, Virolahti municipal centre]
-
A.
isMunicipalityNear
Indicates that one municipality is located close to another municipality or geographic reference point.
-
B.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
C.
municipalityCenterDistance
Indicates the distance between an entity and the central point of its corresponding municipality.
-
D.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
E.
administrativeCentreNearby
chosen
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
- 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_69e77e89d5848190b54352cdb74f6029 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 22, 2026, 9:01 a.m.