Triple
T6750273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weber |
E154323
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Paul Weber
Paul Weber is a relatively common personal name shared by multiple individuals across various professions, such as arts, sports, and academia.
|
E678218
|
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: Paul Weber | Statement: [Weber, hasNotableBearer, Paul Weber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Weber Context triple: [Weber, hasNotableBearer, Paul Weber]
-
A.
Paul Biegler
Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
-
B.
Thomas Weber
Thomas Weber is a relatively common personal name shared by multiple individuals across various professions, including academics, athletes, and public figures.
-
C.
Peter J. Weber
Peter J. Weber was an architect known for his work on the annex of Chicago’s historic Fisher Building.
-
D.
Carl Weiss
Carl Weiss was a Louisiana physician historically known as the alleged assassin of U.S. Senator Huey P. Long in 1935.
-
E.
William Steinkamp
William Steinkamp is an American film editor known for his long-time collaboration with director Sydney Pollack and his work on several acclaimed Hollywood films.
- 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: Paul Weber Triple: [Weber, hasNotableBearer, Paul Weber]
Generated description
Paul Weber is a relatively common personal name shared by multiple individuals across various professions, such as arts, sports, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paul Weber Target entity description: Paul Weber is a relatively common personal name shared by multiple individuals across various professions, such as arts, sports, and academia.
-
A.
Paul Biegler
Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
-
B.
Thomas Weber
Thomas Weber is a relatively common personal name shared by multiple individuals across various professions, including academics, athletes, and public figures.
-
C.
Peter J. Weber
Peter J. Weber was an architect known for his work on the annex of Chicago’s historic Fisher Building.
-
D.
Carl Weiss
Carl Weiss was a Louisiana physician historically known as the alleged assassin of U.S. Senator Huey P. Long in 1935.
-
E.
William Steinkamp
William Steinkamp is an American film editor known for his long-time collaboration with director Sydney Pollack and his work on several acclaimed Hollywood films.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1da32108190882949aa329d2b60 |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8705bf9bc8190aabc53f636c77995 |
completed | March 29, 2026, 12:20 a.m. |
| NEDg | Description generation | batch_69c871d20048819093adce709de55417 |
completed | March 29, 2026, 12:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c873b6e5a88190aa137793a8ec5a47 |
completed | March 29, 2026, 12:35 a.m. |
Created at: March 27, 2026, 2:11 p.m.