Triple
T14568552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ji-Yoon Kim |
E341851
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Amanda Peet |
E81876
|
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: Amanda Peet | Statement: [Ji-Yoon Kim, creator, Amanda Peet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Peet Context triple: [Ji-Yoon Kim, creator, Amanda Peet]
-
A.
Amanda Peet
chosen
Amanda Peet is an American actress known for her work in films like "The Whole Nine Yards" and television series such as "Studio 60 on the Sunset Strip" and "Togetherness."
-
B.
Parker Posey
Parker Posey is an American actress known for her quirky, offbeat roles in independent films of the 1990s, earning her the nickname "Queen of the Indies."
-
C.
Judy Greer
Judy Greer is an American actress known for her versatile supporting roles in film and television, including appearances in major franchises like the Marvel Cinematic Universe.
-
D.
Alison Lohman
Alison Lohman is an American actress known for her roles in films such as Big Fish, White Oleander, and Drag Me to Hell.
-
E.
Michaela Watkins
Michaela Watkins is an American actress and comedian known for her work on "Saturday Night Live" and in numerous television comedies and films.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb38d89fc819086709fd3607b835f |
completed | April 14, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed31670a48190a606e812a2aa0a6e |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 1:23 a.m.