Triple
T2263179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mamie Gummer |
E50084
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mamie Gummer |
E50084
|
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: Mamie Gummer | Statement: [Mamie Gummer, name, Mamie Gummer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mamie Gummer Context triple: [Mamie Gummer, name, Mamie Gummer]
-
A.
Mamie Gummer
chosen
Mamie Gummer is an American actress known for her work in film, television, and theater, and for being the daughter of acclaimed actress Meryl Streep.
-
B.
Grace Gummer
Grace Gummer is an American actress known for her work in film, television, and theater, including roles in series like "Mr. Robot" and "The Newsroom."
-
C.
Don Gummer
Don Gummer is an American sculptor known for his abstract, large-scale works and for his long marriage to actress Meryl Streep.
-
D.
Lizzy Caplan
Lizzy Caplan is an American actress known for her sharp, often comedic roles in film and television, including standout performances in projects like "Mean Girls," "Masters of Sex," and "Cloverfield."
-
E.
Emily Mortimer
Emily Mortimer is a British actress known for her versatile film and television roles, including performances in projects like "Mary Poppins Returns," "Match Point," and "The Newsroom."
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18d7fc08190851765683d1b8092 |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f08f2b88190bba173acb132a160 |
completed | March 9, 2026, 8:04 a.m. |
Created at: March 4, 2026, 7:48 p.m.