Triple
T5098109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Møre og Romsdal |
E114915
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Ulstein
Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
|
E494783
|
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: Ulstein | Statement: [Møre og Romsdal, containsSettlement, Ulstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ulstein Context triple: [Møre og Romsdal, containsSettlement, Ulstein]
-
A.
Gjøa
Gjøa is the historic Norwegian polar exploration ship used by Roald Amundsen to complete the first successful navigation of the Northwest Passage.
-
B.
Mærsk Mc-Kinney Møller
Mærsk Mc-Kinney Møller was a prominent Danish shipping magnate and philanthropist, best known for leading the A.P. Moller–Maersk Group and funding major cultural projects in Denmark.
-
C.
Dukenburg
Dukenburg is a residential district in the southwest of Nijmegen in the Netherlands, known for its post-war urban planning and local railway connectivity.
-
D.
Larsen
Larsen is a surname of Scandinavian origin borne by numerous notable individuals across fields such as literature, music, and sports.
-
E.
MTU Friedrichshafen
MTU Friedrichshafen is a German company specializing in the development and production of high-performance diesel engines and propulsion systems for industrial, marine, and defense applications.
- 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: Ulstein Triple: [Møre og Romsdal, containsSettlement, Ulstein]
Generated description
Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ulstein Target entity description: Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
-
A.
Gjøa
Gjøa is the historic Norwegian polar exploration ship used by Roald Amundsen to complete the first successful navigation of the Northwest Passage.
-
B.
Mærsk Mc-Kinney Møller
Mærsk Mc-Kinney Møller was a prominent Danish shipping magnate and philanthropist, best known for leading the A.P. Moller–Maersk Group and funding major cultural projects in Denmark.
-
C.
Dukenburg
Dukenburg is a residential district in the southwest of Nijmegen in the Netherlands, known for its post-war urban planning and local railway connectivity.
-
D.
Larsen
Larsen is a surname of Scandinavian origin borne by numerous notable individuals across fields such as literature, music, and sports.
-
E.
MTU Friedrichshafen
MTU Friedrichshafen is a German company specializing in the development and production of high-performance diesel engines and propulsion systems for industrial, marine, and defense applications.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7567d21081909227ed8f08b74c71 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba8529ec8190bb1e97eb1044c899 |
completed | March 21, 2026, 3:34 p.m. |
| NEDg | Description generation | batch_69bebc65f37c819088077a02c5a2939e |
completed | March 21, 2026, 3:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bebcc8ad2481909ec38247b32dfdb0 |
completed | March 21, 2026, 3:44 p.m. |
Created at: March 20, 2026, 1:40 p.m.