Triple
T3062083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jepsen |
E62016
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Jan Jepsen
Jan Jepsen is an individual notable enough to be recognized as a prominent bearer of the surname Jepsen.
|
E322703
|
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: Jan Jepsen | Statement: [Jepsen, hasNotableBearer, Jan Jepsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Jepsen Context triple: [Jepsen, hasNotableBearer, Jan Jepsen]
-
A.
Jon Jensen
Jon Jensen is the central protagonist of the film "The Salvation," around whom the story’s dramatic events and conflicts revolve.
-
B.
Jesper Christensen
Jesper Christensen is a Danish actor known internationally for his roles in European cinema and major Hollywood films, including the James Bond series.
-
C.
Kristian Andersen
Kristian Andersen is a prominent Danish-American evolutionary biologist and infectious disease researcher known for his work on viral genomics and the origins and spread of emerging pathogens.
-
D.
Peter Jensen
Peter Jensen is a fictional character appearing in the Danish Western thriller film "The Salvation."
-
E.
Kristian Høgsberg
Kristian Høgsberg is a Danish software engineer best known as the original creator and lead developer of the Wayland display server protocol used in Linux and other Unix-like systems.
- 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: Jan Jepsen Triple: [Jepsen, hasNotableBearer, Jan Jepsen]
Generated description
Jan Jepsen is an individual notable enough to be recognized as a prominent bearer of the surname Jepsen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jan Jepsen Target entity description: Jan Jepsen is an individual notable enough to be recognized as a prominent bearer of the surname Jepsen.
-
A.
Jon Jensen
Jon Jensen is the central protagonist of the film "The Salvation," around whom the story’s dramatic events and conflicts revolve.
-
B.
Jesper Christensen
Jesper Christensen is a Danish actor known internationally for his roles in European cinema and major Hollywood films, including the James Bond series.
-
C.
Kristian Andersen
Kristian Andersen is a prominent Danish-American evolutionary biologist and infectious disease researcher known for his work on viral genomics and the origins and spread of emerging pathogens.
-
D.
Peter Jensen
Peter Jensen is a fictional character appearing in the Danish Western thriller film "The Salvation."
-
E.
Kristian Høgsberg
Kristian Høgsberg is a Danish software engineer best known as the original creator and lead developer of the Wayland display server protocol used in Linux and other Unix-like systems.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e9f33d88190bd481cb7f18ceb91 |
completed | March 8, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ef0e757481908eb1d9693474c49d |
completed | March 11, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69b1efedc68481908c2fece012621f1f |
completed | March 11, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f07505c881909841f184af3e4319 |
completed | March 11, 2026, 10:45 p.m. |
Created at: March 8, 2026, 3:02 p.m.