Triple
T18632648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacobsen |
E455460
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sascha Jacobsen
Sascha Jacobsen is a notable individual, likely recognized for significant contributions in a professional or artistic field.
|
E1334946
|
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: Sascha Jacobsen | Statement: [Jacobsen, hasNotableBearer, Sascha Jacobsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sascha Jacobsen Context triple: [Jacobsen, hasNotableBearer, Sascha Jacobsen]
-
A.
Sascha Schneider
Sascha Schneider was a German Symbolist painter and illustrator known for his allegorical, often homoerotic works and his collaboration on illustrations for Karl May’s adventure novels.
-
B.
Jonas Schneider
Jonas Schneider is a researcher in reinforcement learning best known for co-authoring the Hindsight Experience Replay technique for more efficient learning from sparse rewards.
-
C.
Jonas Dornbach
Jonas Dornbach is a German film producer known for his work on acclaimed international and arthouse cinema.
-
D.
Kai Wiesinger
Kai Wiesinger is a German actor known for his roles in film and television, often appearing in historical dramas and popular German cinema.
-
E.
Jens Schlosser
Jens Schlosser is a cinematographer known for his work on the film "The Salvation."
- 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: Sascha Jacobsen Triple: [Jacobsen, hasNotableBearer, Sascha Jacobsen]
Generated description
Sascha Jacobsen is a notable individual, likely recognized for significant contributions in a professional or artistic field.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sascha Jacobsen Target entity description: Sascha Jacobsen is a notable individual, likely recognized for significant contributions in a professional or artistic field.
-
A.
Sascha Schneider
Sascha Schneider was a German Symbolist painter and illustrator known for his allegorical, often homoerotic works and his collaboration on illustrations for Karl May’s adventure novels.
-
B.
Jonas Schneider
Jonas Schneider is a researcher in reinforcement learning best known for co-authoring the Hindsight Experience Replay technique for more efficient learning from sparse rewards.
-
C.
Jonas Dornbach
Jonas Dornbach is a German film producer known for his work on acclaimed international and arthouse cinema.
-
D.
Kai Wiesinger
Kai Wiesinger is a German actor known for his roles in film and television, often appearing in historical dramas and popular German cinema.
-
E.
Jens Schlosser
Jens Schlosser is a cinematographer known for his work on the film "The Salvation."
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc5c7ec8190ab0c64f009583f96 |
completed | April 19, 2026, 9:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a050d7e812c8190ab055062a4479474 |
completed | May 13, 2026, 11:47 p.m. |
| NEDg | Description generation | batch_6a050fd68c8c8190a34253dd79090280 |
completed | May 13, 2026, 11:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05108fdea081909fd0a1ccdeaeb704 |
completed | May 14, 2026, midnight |
Created at: April 10, 2026, 11:46 a.m.