Triple
T7070817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Wolfe |
E164688
|
entity |
| Predicate | hasRelative |
P367
|
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: [Henry Wolfe, hasRelative, Mamie Gummer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mamie Gummer Context triple: [Henry Wolfe, hasRelative, 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.
Annabelle Wallis
Annabelle Wallis is an English actress known for her roles in television series like Peaky Blinders and films such as Annabelle and The Mummy.
-
E.
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."
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c862f481908d1faf6ed57774f1 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c8a1d788190b9ad25d6e6c460f7 |
completed | March 28, 2026, 9:16 a.m. |
Created at: March 27, 2026, 2:39 p.m.