Triple
T31563166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonkajärvi |
E805325
|
entity |
| Predicate | distanceToHelsinkiApprox |
P21938
|
FINISHED |
| Object | 450 km |
—
|
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: 450 km | Statement: [Sonkajärvi, distanceToHelsinkiApprox, 450 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToHelsinkiApprox Context triple: [Sonkajärvi, distanceToHelsinkiApprox, 450 km]
-
A.
distanceToHelsinki_km
chosen
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Helsinki.
-
B.
distanceToTurkuApproxKm
Indicates an approximate physical distance, measured in kilometers, between a given entity and the city of Turku.
-
C.
distanceToTurku
Indicates the spatial distance between a given entity’s location and the city of Turku.
-
D.
drivingTimeToHelsinkiApprox
Indicates an approximate amount of time it takes to drive from a given location to Helsinki.
-
E.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
- 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_69f348d2ee94819091918d1789398c29 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a01e3a2d0e08190a7d5622920dc56e6 |
completed | May 11, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_6a01e3013e7881909f0cdca25a53c009 |
completed | May 11, 2026, 2:09 p.m. |
Created at: April 30, 2026, 10:16 p.m.