Triple
T1138618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo Metro |
E23196
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Ringen
Ringen is a station on the Oslo Metro system that serves as a key endpoint for certain metro lines in Norway’s capital.
|
E129525
|
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: Ringen | Statement: [Oslo Metro, terminus, Ringen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ringen Context triple: [Oslo Metro, terminus, Ringen]
-
A.
Rycken
Rycken is a Dutch-origin surname historically borne by families such as that of Abraham Rycken in the Low Countries and early colonial America.
-
B.
Trou-ringh
Trou-ringh is a didactic emblem book by Dutch poet and moralist Jacob Cats that offers moral lessons through allegorical illustrations and verse.
-
C.
Veckring
Veckring is a small commune in northeastern France, notable for its proximity to the major Maginot Line fortification of Hackenberg.
-
D.
Kampen
Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
-
E.
Mjölnir MMA
Mjölnir MMA is an Icelandic mixed martial arts gym and training team known for producing high-level fighters such as UFC welterweight Gunnar Nelson.
- 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: Ringen Triple: [Oslo Metro, terminus, Ringen]
Generated description
Ringen is a station on the Oslo Metro system that serves as a key endpoint for certain metro lines in Norway’s capital.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ringen Target entity description: Ringen is a station on the Oslo Metro system that serves as a key endpoint for certain metro lines in Norway’s capital.
-
A.
Rycken
Rycken is a Dutch-origin surname historically borne by families such as that of Abraham Rycken in the Low Countries and early colonial America.
-
B.
Trou-ringh
Trou-ringh is a didactic emblem book by Dutch poet and moralist Jacob Cats that offers moral lessons through allegorical illustrations and verse.
-
C.
Veckring
Veckring is a small commune in northeastern France, notable for its proximity to the major Maginot Line fortification of Hackenberg.
-
D.
Kampen
Kampen is a historic Dutch city known for its well-preserved medieval center and riverside location in the province of Overijssel.
-
E.
Mjölnir MMA
Mjölnir MMA is an Icelandic mixed martial arts gym and training team known for producing high-level fighters such as UFC welterweight Gunnar Nelson.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc25dda481909a26d726fdbdbb50 |
completed | March 1, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac59b020d48190bc6ecbdb720c6779 |
completed | March 7, 2026, 5 p.m. |
| NEDg | Description generation | batch_69ac5a7599048190a46b0d560270ffa4 |
completed | March 7, 2026, 5:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5af24a948190a37c832508149a48 |
completed | March 7, 2026, 5:05 p.m. |
Created at: March 1, 2026, 7:44 p.m.