Triple
T8662454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Kiel |
E205579
|
entity |
| Predicate | hasTerminal |
P182
|
FINISHED |
| Object |
Schwedenkai
Schwedenkai is a passenger and cargo ferry terminal in the Port of Kiel, Germany, primarily serving routes to and from Sweden.
|
E749191
|
NE FINISHED |
How this triple was built (4 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: Schwedenkai | Statement: [Port of Kiel, hasTerminal, Schwedenkai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwedenkai Context triple: [Port of Kiel, hasTerminal, Schwedenkai]
-
A.
Storholmen
Storholmen is an island located in Lake Femunden, one of Norway’s largest inland lakes.
-
B.
Anholt Havn
Anholt Havn is the main harbor and marina on the Danish island of Anholt, serving as its key hub for fishing, transport, and visiting yachts in the Kattegat.
-
C.
Sollentuna
Sollentuna is a suburban town in Stockholm County, Sweden, known as part of the Stockholm urban area and a residential and commercial hub just north of the capital.
-
D.
Kristineberg
Kristineberg is a residential neighborhood in the western part of central Stockholm, known for its waterfront location and green areas.
-
E.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Schwedenkai Triple: [Port of Kiel, hasTerminal, Schwedenkai]
Generated description
Schwedenkai is a passenger and cargo ferry terminal in the Port of Kiel, Germany, primarily serving routes to and from Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schwedenkai Target entity description: Schwedenkai is a passenger and cargo ferry terminal in the Port of Kiel, Germany, primarily serving routes to and from Sweden.
-
A.
Storholmen
Storholmen is an island located in Lake Femunden, one of Norway’s largest inland lakes.
-
B.
Anholt Havn
Anholt Havn is the main harbor and marina on the Danish island of Anholt, serving as its key hub for fishing, transport, and visiting yachts in the Kattegat.
-
C.
Sollentuna
Sollentuna is a suburban town in Stockholm County, Sweden, known as part of the Stockholm urban area and a residential and commercial hub just north of the capital.
-
D.
Kristineberg
Kristineberg is a residential neighborhood in the western part of central Stockholm, known for its waterfront location and green areas.
-
E.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
- F. None of above. chosen
Provenance (5 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4872a190819087d679f3006bd030 |
completed | March 31, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecd0518248190ba0d3a87d11dff86 |
completed | April 2, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69cece8e5afc8190912b6eb9c80dd073 |
completed | April 2, 2026, 8:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecf8ee4f48190bb901e35ade91b6c |
completed | April 2, 2026, 8:20 p.m. |
Created at: March 30, 2026, 6:30 p.m.