Triple
T278763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Curtis |
E5307
|
entity |
| Predicate | coWriterOf |
P2389
|
FINISHED |
| Object | Mr. Bean |
E36279
|
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: Mr. Bean | Statement: [Richard Curtis, coWriterOf, Mr. Bean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Bean Context triple: [Richard Curtis, coWriterOf, Mr. Bean]
-
A.
Mr. Bean
chosen
Mr. Bean is a largely silent, bumbling British comedy character known for his childlike antics and visual gags in the television series and films of the same name.
-
B.
Bert
Bert is the given name of Bert Hölldobler, a renowned German behavioral biologist and sociobiologist known for his pioneering research on ants and social insects.
-
C.
Monty
Monty is the nickname of British Field Marshal Bernard Law Montgomery, a prominent World War II commander best known for his leadership in the North African and European campaigns.
-
D.
Norman Wisdom
Norman Wisdom was a beloved English comedian, actor, and singer best known for his slapstick film roles in the mid-20th century, particularly as the character Norman Pitkin.
-
E.
Uncle Fred
Uncle Fred is a mischievous, quick-witted aristocrat and recurring comic hero in P. G. Wodehouse’s humorous stories.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a260d0dae48190a2ec98d0186fd792 |
completed | Feb. 28, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a399a5913c819082fac6bb344bd585 |
completed | March 1, 2026, 1:43 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.