Triple
T2487036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridesmaids |
E55949
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Rebel Wilson |
E199363
|
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: Rebel Wilson | Statement: [Bridesmaids, starring, Rebel Wilson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebel Wilson Context triple: [Bridesmaids, starring, Rebel Wilson]
-
A.
Rebel Wilson
chosen
Rebel Wilson is an Australian actress and comedian known for her scene-stealing roles in films like Pitch Perfect and Bridesmaids.
-
B.
Anna Faris
Anna Faris is an American actress and comedian best known for her lead role in the Scary Movie film series and her work in both film and television comedy.
-
C.
Natasha Lyonne
Natasha Lyonne is an American actress, writer, and director known for her distinctive raspy voice and roles in projects like Russian Doll, the American Pie films, and various acclaimed independent movies.
-
D.
Samantha Barks
Samantha Barks is a Manx actress and singer best known for her role as Éponine in the 2012 film adaptation of "Les Misérables" and her work in musical theatre.
-
E.
Emma Stone
Emma Stone is an American actress acclaimed for her versatile performances in films such as "La La Land," for which she won the Academy Award for Best Actress.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1782ca081909645164a6acf0ea0 |
completed | March 7, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af17bca6f88190a63672fb3372f0be |
completed | March 9, 2026, 6:55 p.m. |
Created at: March 6, 2026, 9:45 p.m.