Triple
T11719691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuser family |
E278593
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object | John Dryden Kuser |
E58056
|
NE FINISHED |
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: John Dryden Kuser | Statement: [Kuser family, hasNotableMember, John Dryden Kuser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Dryden Kuser Context triple: [Kuser family, hasNotableMember, John Dryden Kuser]
-
A.
John Dryden Kuser
chosen
John Dryden Kuser was an American politician and socialite from a prominent New Jersey family, known in part for his brief and troubled early marriage to philanthropist Brooke Astor.
-
B.
Mr. Dryden
Mr. Dryden is a British government official in the film "Lawrence of Arabia" who helps orchestrate T.E. Lawrence’s assignment in the Arab Revolt.
-
C.
John F. Dryden
John F. Dryden was an American businessman and politician who pioneered industrial life insurance in the United States and served as a U.S. Senator from New Jersey.
-
D.
Dryden
Dryden is a surname most famously associated with Ken Dryden, the Hall of Fame Canadian ice hockey goaltender and former politician.
-
E.
Dryden
Dryden is a small city in northwestern Ontario, Canada, known historically for its forestry and paper mill industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c26e4c8190ae30d906b4fd4221 |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0197d03c08190a5515ffe3cc887ea |
completed | April 28, 2026, 2:20 a.m. |
Created at: April 8, 2026, 9:40 p.m.