Triple
T7371483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manfred R. Schroeder |
E170014
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Schroeder
Schroeder is a German surname borne by numerous notable individuals across fields such as science, politics, and the arts.
|
E322341
|
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: Schroeder | Statement: [Manfred R. Schroeder, familyName, Schroeder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schroeder Context triple: [Manfred R. Schroeder, familyName, Schroeder]
-
A.
Schroeder
Schroeder is a character from the Peanuts comic strip known for his serious devotion to playing the piano and his admiration for Beethoven.
-
B.
Scheer
Scheer is a German surname most notably associated with Reinhard Scheer, a high-ranking Imperial German Navy admiral during World War I.
-
C.
Sanders
Sanders is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
-
D.
Kurt Schröder
Kurt Schröder was a German film composer known for scoring early 20th-century European films, including notable British historical dramas.
-
E.
Michael Schroeder
Michael Schroeder is a software developer best known for his work on the GNU Screen terminal multiplexer.
- 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: Schroeder Triple: [Manfred R. Schroeder, familyName, Schroeder]
Generated description
Schroeder is a German surname borne by numerous notable individuals across fields such as science, politics, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schroeder Target entity description: Schroeder is a German surname borne by numerous notable individuals across fields such as science, politics, and the arts.
-
A.
Schroeder
chosen
Schroeder is a character from the Peanuts comic strip known for his serious devotion to playing the piano and his admiration for Beethoven.
-
B.
Scheer
Scheer is a German surname most notably associated with Reinhard Scheer, a high-ranking Imperial German Navy admiral during World War I.
-
C.
Sanders
Sanders is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
-
D.
Kurt Schröder
Kurt Schröder was a German film composer known for scoring early 20th-century European films, including notable British historical dramas.
-
E.
Michael Schroeder
Michael Schroeder is a software developer best known for his work on the GNU Screen terminal multiplexer.
- F. None of above.
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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f18451d88190ad4a2674279bb703 |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802c711788190806987567dbc9942 |
completed | March 28, 2026, 4:33 p.m. |
| NEDg | Description generation | batch_69c8035151a481908a33c1ecd12c2f6d |
completed | March 28, 2026, 4:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c803aea0808190a5208c02a0db1187 |
completed | March 28, 2026, 4:37 p.m. |
Created at: March 27, 2026, 3:07 p.m.