Triple
T8662455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Kiel |
E205579
|
entity |
| Predicate | hasTerminal |
P182
|
FINISHED |
| Object |
Norwegenkai
Norwegenkai is a passenger and freight ferry terminal in Kiel, Germany, primarily serving routes between Germany and Norway.
|
E750988
|
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: Norwegenkai | Statement: [Port of Kiel, hasTerminal, Norwegenkai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norwegenkai Context triple: [Port of Kiel, hasTerminal, Norwegenkai]
-
A.
Mykland
Mykland is a small village in Agder county, Norway, known for its rural setting and surrounding forests and lakes.
-
B.
Vestland
Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
-
C.
Oscar II Land
Oscar II Land is a peninsula on the western side of Spitsbergen in the Svalbard archipelago, characterized by glaciated terrain and Arctic coastal landscapes.
-
D.
Norheimsund
Norheimsund is a village in western Norway known as a regional center in the Hardanger region, noted for its scenic fjordside setting and proximity to the Steinsdalsfossen waterfall.
-
E.
Oslo archipelago
The Oslo archipelago is a scenic collection of islands and skerries in the Oslofjord, popular for boating, swimming, and outdoor recreation near Norway’s capital.
- 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: Norwegenkai Triple: [Port of Kiel, hasTerminal, Norwegenkai]
Generated description
Norwegenkai is a passenger and freight ferry terminal in Kiel, Germany, primarily serving routes between Germany and Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Norwegenkai Target entity description: Norwegenkai is a passenger and freight ferry terminal in Kiel, Germany, primarily serving routes between Germany and Norway.
-
A.
Mykland
Mykland is a small village in Agder county, Norway, known for its rural setting and surrounding forests and lakes.
-
B.
Vestland
Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
-
C.
Oscar II Land
Oscar II Land is a peninsula on the western side of Spitsbergen in the Svalbard archipelago, characterized by glaciated terrain and Arctic coastal landscapes.
-
D.
Norheimsund
Norheimsund is a village in western Norway known as a regional center in the Hardanger region, noted for its scenic fjordside setting and proximity to the Steinsdalsfossen waterfall.
-
E.
Oslo archipelago
The Oslo archipelago is a scenic collection of islands and skerries in the Oslofjord, popular for boating, swimming, and outdoor recreation near Norway’s capital.
- 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_69cef37efbf08190805fbb270a4bce37 |
completed | April 2, 2026, 10:53 p.m. |
| NEDg | Description generation | batch_69cef5c38c9481908b5b5d30f5335abd |
completed | April 2, 2026, 11:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cef6cd52f88190b76c44e73c2e1ab4 |
completed | April 2, 2026, 11:07 p.m. |
Created at: March 30, 2026, 6:30 p.m.