Triple
T5693126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Moms |
E125472
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Annie Mumolo |
E271300
|
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: Annie Mumolo | Statement: [Bad Moms, starring, Annie Mumolo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annie Mumolo Context triple: [Bad Moms, starring, Annie Mumolo]
-
A.
Annie Mumolo
chosen
Annie Mumolo is an American actress, comedian, and writer best known for co-writing the hit comedy film "Bridesmaids" with Kristen Wiig.
-
B.
Lauren Shuler Donner
Lauren Shuler Donner is an American film producer best known for her work on major studio films including the X-Men franchise and other popular Hollywood features.
-
C.
Ari Wegner
Ari Wegner is an acclaimed Australian cinematographer known for her visually striking work on films such as "The Power of the Dog."
-
D.
Molly Gordon
Molly Gordon is an American actress and director known for her roles in films like "Booksmart" and "Good Boys" and the TV series "The Bear."
-
E.
Molly Messick
Molly Messick is an American audio producer and journalist known for her work in public radio and podcasting.
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e678c48190824d35d276985311 |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a4f2bfc8190bc56c094f9ae9ce1 |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:44 p.m.