Triple
T29385183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korpo |
E745230
|
entity |
| Predicate | distanceToTurkuApproxKm |
P202465
|
FINISHED |
| Object | 60–80 |
—
|
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: 60–80 | Statement: [Korpo, distanceToTurkuApproxKm, 60–80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTurkuApproxKm Context triple: [Korpo, distanceToTurkuApproxKm, 60–80]
-
A.
distanceToTurku
Indicates the spatial distance between a given entity’s location and the city of Turku.
-
B.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
-
C.
distanceToHelsinki_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Helsinki.
-
D.
distanceToOulu_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Oulu.
-
E.
distanceToTampere
Indicates the measured or calculated distance between a given entity’s location and the city of Tampere.
- F. None of above. chosen
Provenance (4 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a0082989e6c819099fea0e706332e37 |
completed | May 10, 2026, 1:05 p.m. |
| PD | Predicate disambiguation | batch_6a0081ed6a1481908baf472876e28db9 |
completed | May 10, 2026, 1:02 p.m. |
| PDg | Predicate description generation | batch_6a008297ad4c81909ee2e713d2c754d1 |
completed | May 10, 2026, 1:05 p.m. |
Created at: April 28, 2026, 2:38 p.m.