Triple
T12033469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E. Howard Hunt |
E286470
|
entity |
| Predicate | hasPseudonym |
P3799
|
FINISHED |
| Object | Robert Dietrich |
E286470
|
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: Robert Dietrich | Statement: [E. Howard Hunt, hasPseudonym, Robert Dietrich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Dietrich Context triple: [E. Howard Hunt, hasPseudonym, Robert Dietrich]
-
A.
Robert Dietrich
chosen
Robert Dietrich is a pseudonym used by E. Howard Hunt, an American intelligence officer and author known for his role in the Watergate scandal.
-
B.
William Diehl
William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
-
C.
Robert Schrader
Robert Schrader is a mathematical physicist best known for co-developing the Osterwalder–Schrader axioms, which provide a rigorous foundation for Euclidean quantum field theory.
-
D.
Paul Dietrich
Paul Dietrich is an architect best known as one of the founders of the design and planning firm Cambridge Seven Associates.
-
E.
Richard Riehle
Richard Riehle is an American character actor known for his prolific work in film and television, including memorable roles in movies like "Office Space" and numerous guest appearances on popular TV series.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040724ec8190808f334013ddc6d6 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbac5b0881908cc98458f1b3004d |
completed | May 3, 2026, 4:14 a.m. |
Created at: April 8, 2026, 9:47 p.m.