Triple
T22794462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eugene Roche |
E564204
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Eugene Roche |
—
|
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: Eugene Roche | Statement: [Eugene Roche, name, Eugene Roche]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eugene Roche Context triple: [Eugene Roche, name, Eugene Roche]
-
A.
Eugene Roche
chosen
Eugene Roche was an American character actor known for his prolific work in film and television, often playing affable or comedic supporting roles.
-
B.
Eugene Maurice
Eugene Maurice was a 17th-century French nobleman and military commander who held the title of Count of Soissons.
-
C.
Charles Rochon
Charles Rochon was an early French settler and landowner in the Mobile, Alabama area, recognized as one of the region’s foundational colonial figures.
-
D.
Gerald Roche
Gerald Roche is a scholar and linguist known for his research on the Monguor (Tu) language and the sociolinguistics of minority languages in China.
-
E.
Louis Tully
Louis Tully is a nerdy, well-meaning accountant and neighbor of Dana Barrett who becomes a comedic, possessed pawn of Gozer in the Ghostbusters films.
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cd81794819091b528600e322d7b |
completed | April 29, 2026, 3:36 a.m. |
Created at: April 17, 2026, 3:30 p.m.