Triple
T2487033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridesmaids |
E55949
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ellie Kemper |
E223037
|
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: Ellie Kemper | Statement: [Bridesmaids, starring, Ellie Kemper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellie Kemper Context triple: [Bridesmaids, starring, Ellie Kemper]
-
A.
Ellie Kemper
chosen
Ellie Kemper is an American actress and comedian best known for her roles in the sitcoms "The Office" and "Unbreakable Kimmy Schmidt."
-
B.
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.
-
C.
Alison Brie
Alison Brie is an American actress known for her roles in television series like "Community" and "Mad Men," as well as her voice work in animated films.
-
D.
Kaitlin Olson
Kaitlin Olson is an American actress and comedian best known for playing Dee Reynolds on the long-running sitcom "It's Always Sunny in Philadelphia."
-
E.
Kat Dennings
Kat Dennings is an American actress best known for her roles in the sitcom "2 Broke Girls" and films such as "Nick and Norah's Infinite Playlist" and the Marvel "Thor" 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_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.