Triple
T25548312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockholm Skavsta Airport |
E640368
|
entity |
| Predicate | distanceFromNyköping |
P182377
|
FINISHED |
| Object | about 7 kilometres northwest of Nyköping |
—
|
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: about 7 kilometres northwest of Nyköping | Statement: [Stockholm Skavsta Airport, distanceFromNyköping, about 7 kilometres northwest of Nyköping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNyköping Context triple: [Stockholm Skavsta Airport, distanceFromNyköping, about 7 kilometres northwest of Nyköping]
-
A.
distanceFromUppsala_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Uppsala.
-
B.
distanceFromStockholmCityCentre
Indicates the measured distance between a given location and the center of Stockholm city.
-
C.
distanceFromKungstradgarden_km
Indicates the distance, measured in kilometers, from Kungsträdgården to a given location.
-
D.
distanceToEskilstuna
Indicates the spatial distance between a given entity and the location Eskilstuna.
-
E.
distanceFromGävle
Indicates the spatial distance between a given entity and the location of Gävle.
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f78d7211a48190bfb59c406f0bf12f |
completed | May 3, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c6014e08190864785a4fe3e8e73 |
completed | May 3, 2026, 5:56 p.m. |
Created at: April 21, 2026, 3:35 p.m.