Triple
T6828981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Post |
E157087
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Alison Brie |
E80154
|
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: Alison Brie | Statement: [The Post, starredActor, Alison Brie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alison Brie Context triple: [The Post, starredActor, Alison Brie]
-
A.
Alison Brie
chosen
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.
-
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.
Ellie Kemper
Ellie Kemper is an American actress and comedian best known for her roles in the sitcoms "The Office" and "Unbreakable Kimmy Schmidt."
-
D.
Maya Erskine
Maya Erskine is an American actress, writer, and comedian best known for co-creating and starring in the cringe-comedy series "PEN15."
-
E.
Zooey Deschanel
Zooey Deschanel is an American actress, singer, and songwriter known for her quirky, offbeat roles in films like "500 Days of Summer" and the TV series "New Girl."
- 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6254bd88190a2a424537c2c12e2 |
completed | March 27, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723f73eec81908c666888a19c0b29 |
completed | March 28, 2026, 12:42 a.m. |
Created at: March 27, 2026, 2:18 p.m.