Triple
T4688392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwab |
E103974
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Martin Schwab
Martin Schwab is a German actor known for his extensive work in theater, film, and television.
|
E471744
|
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: Martin Schwab | Statement: [Schwab, hasNotableBearer, Martin Schwab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Schwab Context triple: [Schwab, hasNotableBearer, Martin Schwab]
-
A.
Michael Schwab
Michael Schwab was a German-American labor activist and anarchist who became one of the convicted Haymarket Affair defendants in 1886.
-
B.
Sidney Schwab
Sidney Schwab is an individual notable enough to be recognized as a prominent bearer of the Schwab surname.
-
C.
Charles R. Schwab
Charles R. Schwab is an American investor and businessman best known as the founder of the Charles Schwab Corporation, a pioneering discount brokerage firm.
-
D.
Charles M. Schwab
Charles M. Schwab was a prominent American steel magnate and businessman who led Bethlehem Steel to become one of the largest steel producers in the world in the early 20th century.
-
E.
Stuart Schwab
Stuart Schwab is an American legal scholar and former dean of Cornell Law School known for his work in employment law and economic analysis of law.
- 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: Martin Schwab Triple: [Schwab, hasNotableBearer, Martin Schwab]
Generated description
Martin Schwab is a German actor known for his extensive work in theater, film, and television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martin Schwab Target entity description: Martin Schwab is a German actor known for his extensive work in theater, film, and television.
-
A.
Michael Schwab
Michael Schwab was a German-American labor activist and anarchist who became one of the convicted Haymarket Affair defendants in 1886.
-
B.
Sidney Schwab
Sidney Schwab is an individual notable enough to be recognized as a prominent bearer of the Schwab surname.
-
C.
Charles R. Schwab
Charles R. Schwab is an American investor and businessman best known as the founder of the Charles Schwab Corporation, a pioneering discount brokerage firm.
-
D.
Charles M. Schwab
Charles M. Schwab was a prominent American steel magnate and businessman who led Bethlehem Steel to become one of the largest steel producers in the world in the early 20th century.
-
E.
Stuart Schwab
Stuart Schwab is an American legal scholar and former dean of Cornell Law School known for his work in employment law and economic analysis of law.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6397f6888190a9024a51d4d34f2b |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4d7ad90c8190b6f36472a209a0f9 |
completed | March 21, 2026, 7:49 a.m. |
| NEDg | Description generation | batch_69be4f0a6f548190beb90be3c17611a6 |
completed | March 21, 2026, 7:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be4f623e808190969536dce2db2e35 |
completed | March 21, 2026, 7:57 a.m. |
Created at: March 20, 2026, 1:16 p.m.