Triple
T7069386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyköping |
E164645
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object | Nyköping harbor |
E640369
|
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: Nyköping harbor | Statement: [Nyköping, hasPort, Nyköping harbor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyköping harbor Context triple: [Nyköping, hasPort, Nyköping harbor]
-
A.
Nyköping harbor
chosen
Nyköping harbor is a scenic waterfront area in the Swedish town of Nyköping, known for its marina, promenades, restaurants, and access to the Baltic Sea archipelago.
-
B.
Strömstad harbor
Strömstad harbor is a coastal port area in the Swedish town of Strömstad, known for its ferry connections, boating activities, and access to the surrounding archipelago.
-
C.
Borgholm harbor
Borgholm harbor is a small coastal port and marina serving the town of Borgholm on the Swedish island of Öland, known for leisure boating and tourism.
-
D.
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.
-
E.
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.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4aa82108190bacd5584c1c78999 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c8a1d788190b9ad25d6e6c460f7 |
completed | March 28, 2026, 9:16 a.m. |
Created at: March 27, 2026, 2:39 p.m.