Triple
T33164980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George E. Chamberlain |
E848855
|
entity |
| Predicate | succeededByAsGovernorOfOregon |
P83713
|
FINISHED |
| Object | Frank W. Benson |
—
|
NE NERFINISHED |
How this triple was built (2 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: Frank W. Benson | Statement: [George E. Chamberlain, succeededByAsGovernorOfOregon, Frank W. Benson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: succeededByAsGovernorOfOregon Context triple: [George E. Chamberlain, succeededByAsGovernorOfOregon, Frank W. Benson]
-
A.
succeededBy (Governor of California)
Indicates that one individual directly follows another in holding the office of Governor of California.
-
B.
succeededByAsGovernorOfIndiana
Indicates that one person directly followed another in holding the office of Governor of Indiana.
-
C.
succeededInOfficeAsGovernorBy
chosen
Indicates that one individual’s term as governor ended and was directly followed by another individual’s term in the same office.
-
D.
succeededBy (Governor of Vermont)
Indicates that one individual directly followed another in holding the office of Governor of Vermont.
-
E.
succeededBy (Governor of Maine)
Indicates that one individual directly follows another in holding the office of Governor of Maine.
- F. None of above.
Provenance (3 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_69f3495be8808190bbf427733df08aad |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff7dcedab08190a719a707d03306e2 |
completed | May 9, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69ff7d0119348190ad462554e81190fe |
completed | May 9, 2026, 6:29 p.m. |
Created at: May 1, 2026, 1:28 a.m.