Triple
T21052823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almedalen park |
E518631
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Visby harbour |
—
|
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: Visby harbour | Statement: [Almedalen park, near, Visby harbour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Visby harbour Context triple: [Almedalen park, near, Visby harbour]
-
A.
Port of Visby
chosen
The Port of Visby is the main commercial and passenger harbor of Visby on the Swedish island of Gotland, serving as a key hub for Baltic Sea ferry traffic and tourism.
-
B.
Visby
Visby is a well-preserved medieval Hanseatic town on the Swedish island of Gotland, renowned for its historic city wall and UNESCO World Heritage status.
-
C.
Port of Kalmar
The Port of Kalmar is a Swedish Baltic Sea harbor serving the city of Kalmar with facilities for cargo handling, passenger traffic, and regional maritime trade.
-
D.
Port of Oxelösund
The Port of Oxelösund is a major Swedish Baltic Sea port known for its deep-water facilities and significant role in handling bulk cargo, particularly for the steel industry.
-
E.
Port of Halmstad
The Port of Halmstad is a commercial seaport in Halmstad, Sweden, handling cargo, logistics, and maritime traffic along the country’s west coast.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7cabe881909e6b258a14d501a6 |
completed | April 21, 2026, 4:30 a.m. |
Created at: April 16, 2026, 2:35 p.m.