Triple
T13799322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Vänern |
E331596
|
entity |
| Predicate | hasCityOnShore |
P969
|
FINISHED |
| Object | Mariestad |
E504210
|
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: Mariestad | Statement: [Lake Vänern, hasCityOnShore, Mariestad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mariestad Context triple: [Lake Vänern, hasCityOnShore, Mariestad]
-
A.
Mariestad
chosen
Mariestad is a small historic town in southern Sweden, located on the shores of Lake Vänern and known for its well-preserved old center and lakeside setting.
-
B.
Halmstad
Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
-
C.
Halmstad
Halmstad is a village in Moss municipality in Viken county, southeastern Norway.
-
D.
Malmö
Malmö is a major coastal city in southern Sweden known for its historic center, modern architecture like the Turning Torso, and its role as a cultural and economic hub connected to Copenhagen via the Öresund Bridge.
-
E.
Gothenburg
Gothenburg is Sweden’s second-largest city, a major port on the country’s west coast known for its maritime heritage, universities, and vibrant cultural scene.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ce9148190b23370f6a522ff7a |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe249c57bc819089baed544fb8fead |
completed | May 8, 2026, 5:59 p.m. |
Created at: April 9, 2026, 10:11 p.m.