Triple
T22683262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Västerås Line |
E560837
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Enköping |
—
|
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: Enköping | Statement: [Västerås Line, passesThrough, Enköping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enköping Context triple: [Västerås Line, passesThrough, Enköping]
-
A.
Enköping
chosen
Enköping is a small Swedish town known for its numerous themed parks and gardens, often called “Sweden’s nearest town” due to its central location relative to several major cities.
-
B.
Nyköping
Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
-
C.
Södertälje
Södertälje is a Swedish city southwest of Stockholm known for its industrial heritage, diverse population, and strategic location linking Lake Mälaren with the Baltic Sea via the Södertälje Canal.
-
D.
Norrköping
Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
-
E.
Eskilstuna
Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1786204d88190a837a5f04e16e94c |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 3:12 p.m.