Triple
T13701151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pest |
E328519
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jeffrey Jones |
E15667
|
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: Jeffrey Jones | Statement: [The Pest, starring, Jeffrey Jones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Jones Context triple: [The Pest, starring, Jeffrey Jones]
-
A.
Jeffrey Jones
chosen
Jeffrey Jones is an American character actor best known for his roles in films such as "Ferris Bueller's Day Off," "Beetlejuice," and "Amadeus."
-
B.
Joseph Marcell
Joseph Marcell is a British actor best known for playing the witty butler Geoffrey Butler on the sitcom "The Fresh Prince of Bel-Air."
-
C.
Michael Pennington
Michael Pennington is a distinguished English actor and director, particularly renowned for his work in classical theatre and Shakespearean performance.
-
D.
Eric Warner
Eric Warner is a relatively obscure individual whose primary distinguishing feature is sharing the common surname Warner, with no widely recognized public achievements or roles documented.
-
E.
Jeffery Wood
Jeffery Wood is an American actor best known for his role on the television sitcom "In the House."
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc879adc88190b03f1cf815b71061 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a8437af481909f91bb41bfdac53a |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:54 p.m.