Triple
T22037035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman Kahn |
E544237
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Herman Kahn |
—
|
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: Herman Kahn | Statement: [Herman Kahn, name, Herman Kahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herman Kahn Context triple: [Herman Kahn, name, Herman Kahn]
-
A.
Herman Kahn
chosen
Herman Kahn was an American military strategist and futurist best known for his work on nuclear strategy and for founding the Hudson Institute.
-
B.
Albert Wohlstetter
Albert Wohlstetter was an influential American nuclear strategist and defense intellectual whose work on deterrence and military policy shaped generations of U.S. policymakers and strategists.
-
C.
Bernard Brodie
Bernard Brodie was an American military strategist and nuclear theorist whose work helped shape Cold War deterrence doctrine and modern strategic studies.
-
D.
Ken Ledeen
Ken Ledeen is a technology entrepreneur and author best known for co-writing influential works on digital technology and its societal impact.
-
E.
Ethan Dulles
Ethan Dulles is the central protagonist of the film "Slackers," around whom the story’s comedic misadventures revolve.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f32edc81909b6898af6621f56f |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:25 p.m.