Triple
T18597555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midttrafik |
E454531
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object |
Samsø
Samsø is a Danish island in the Kattegat Sea known for its pioneering use of renewable energy and sustainable community initiatives.
|
E1333047
|
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: Samsø | Statement: [Midttrafik, operatesIn, Samsø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samsø Context triple: [Midttrafik, operatesIn, Samsø]
-
A.
Mandø
Mandø is a small Danish island in the Wadden Sea, known for its tidal causeway access, rich birdlife, and traditional marshland landscapes.
-
B.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
-
C.
Gødland
Gødland is a psychedelic, retro-styled science fiction comic book series that pays homage to classic cosmic superhero tales, created by writer Joe Casey and artist Tom Scioli.
-
D.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
E.
Skarø
Skarø is a small Danish island in the Baltic Sea known for its scenic landscapes, birdlife, and popular summer ice cream and music festival.
- 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: Samsø Triple: [Midttrafik, operatesIn, Samsø]
Generated description
Samsø is a Danish island in the Kattegat Sea known for its pioneering use of renewable energy and sustainable community initiatives.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samsø Target entity description: Samsø is a Danish island in the Kattegat Sea known for its pioneering use of renewable energy and sustainable community initiatives.
-
A.
Mandø
Mandø is a small Danish island in the Wadden Sea, known for its tidal causeway access, rich birdlife, and traditional marshland landscapes.
-
B.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
-
C.
Gødland
Gødland is a psychedelic, retro-styled science fiction comic book series that pays homage to classic cosmic superhero tales, created by writer Joe Casey and artist Tom Scioli.
-
D.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
E.
Skarø
Skarø is a small Danish island in the Baltic Sea known for its scenic landscapes, birdlife, and popular summer ice cream and music festival.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474d934481909b4afd5ef9031c73 |
completed | April 19, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05037eda788190977fcb50aa4d2357 |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a0504cd76388190b67c78250297573d |
completed | May 13, 2026, 11:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0505482c588190952fe07726f64b93 |
completed | May 13, 2026, 11:12 p.m. |
Created at: April 10, 2026, 11:44 a.m.