Triple
T15501224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red line (Stockholm metro) |
E378957
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Slussen |
E378958
|
NE 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: Slussen | Statement: [Red line (Stockholm metro), hasStation, Slussen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slussen Context triple: [Red line (Stockholm metro), hasStation, Slussen]
-
A.
Slussen
chosen
Slussen is a major transport hub and metro station in central Stockholm, serving as a key interchange between multiple subway lines and other public transit.
-
B.
Kolsås
Kolsås is a suburban area in Bærum, Norway, known as the endpoint of one of the Oslo Metro lines and for its nearby forested hill popular for hiking and climbing.
-
C.
Brunkebergstorg
Brunkebergstorg is a central public square in downtown Stockholm known for its financial institutions, modern architecture, and role as a key urban meeting place.
-
D.
Lilla Nygatan
Lilla Nygatan is a historic street in Stockholm’s Old Town (Gamla stan), known for its preserved medieval character and traditional urban streetscape.
-
E.
Fridhemsplan
Fridhemsplan is a major public square and transport hub in central Stockholm, known for its busy metro interchange and surrounding commercial area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcb4e8c81908e4ab463e3ae252b |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d4a9bf88190b7c6b4874abe165f |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:54 a.m.