Triple
T5752136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Ronson |
E126876
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Grace Gummer |
E50667
|
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: Grace Gummer | Statement: [Mark Ronson, spouse, Grace Gummer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grace Gummer Context triple: [Mark Ronson, spouse, Grace Gummer]
-
A.
Grace Gummer
chosen
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."
-
B.
Mamie Gummer
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.
-
C.
Jemima Kirke
Jemima Kirke is a British-American artist and actress best known for playing Jessa Johansson on the HBO series "Girls."
-
D.
Natascha McElhone
Natascha McElhone is a British actress known for her film roles in the late 1990s and 2000s, including prominent performances in movies like "The Truman Show" and "Ronin," as well as her work in television series such as "Californication."
-
E.
Jessica Lucas
Jessica Lucas is a Canadian actress known for her roles in film and television, including prominent appearances in projects like the monster movie "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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0288b580c81909e1289982b106695 |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0bf9968d881908ef4065d1d13b2b8 |
completed | March 23, 2026, 4:20 a.m. |
Created at: March 22, 2026, 3:48 p.m.