Triple
T19065837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutger |
E466655
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object |
Rüdiger
Rüdiger is a German given name of Germanic origin, commonly used as a masculine first name in German-speaking countries.
|
E1356945
|
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: Rüdiger | Statement: [Rutger, hasCognate, Rüdiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rüdiger Context triple: [Rutger, hasCognate, Rüdiger]
-
A.
Wolf Rüdiger
Wolf Rüdiger was a German architect and author best known as the son of Rudolf Hess and for his controversial efforts to rehabilitate his father's reputation.
-
B.
Rudi Jäger
Rudi Jäger is a sadistic Nazi prison warden and antagonist in the video game Wolfenstein: The Old Blood, known for hunting the protagonist with his attack dogs.
-
C.
Reinhard
Reinhard is a masculine German given name historically borne by several notable figures, including high-ranking officials in Nazi Germany.
-
D.
Jürgen
Jürgen is a masculine given name of German origin, commonly used in German-speaking countries.
-
E.
Erich Roland
Erich Roland is a cinematographer known for his work on the documentary film "He Named Me Malala."
- 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: Rüdiger Triple: [Rutger, hasCognate, Rüdiger]
Generated description
Rüdiger is a German given name of Germanic origin, commonly used as a masculine first name in German-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rüdiger Target entity description: Rüdiger is a German given name of Germanic origin, commonly used as a masculine first name in German-speaking countries.
-
A.
Wolf Rüdiger
Wolf Rüdiger was a German architect and author best known as the son of Rudolf Hess and for his controversial efforts to rehabilitate his father's reputation.
-
B.
Rudi Jäger
Rudi Jäger is a sadistic Nazi prison warden and antagonist in the video game Wolfenstein: The Old Blood, known for hunting the protagonist with his attack dogs.
-
C.
Reinhard
Reinhard is a masculine German given name historically borne by several notable figures, including high-ranking officials in Nazi Germany.
-
D.
Jürgen
Jürgen is a masculine given name of German origin, commonly used in German-speaking countries.
-
E.
Erich Roland
Erich Roland is a cinematographer known for his work on the documentary film "He Named Me Malala."
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e198621481908618f65dd01746fc |
completed | April 20, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05d3586fc88190b7e48c4afb767a2a |
completed | May 14, 2026, 1:51 p.m. |
| NEDg | Description generation | batch_6a05d430aabc8190bdf30a16700e2476 |
completed | May 14, 2026, 1:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05d4e41f108190a2d7a3a60d1e3b87 |
completed | May 14, 2026, 1:57 p.m. |
Created at: April 10, 2026, 12:03 p.m.