Triple
T18508565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Girls Revolt |
E452267
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Dana Calvo |
—
|
NE NERFINISHED |
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: Dana Calvo | Statement: [Good Girls Revolt, creator, Dana Calvo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Calvo Context triple: [Good Girls Revolt, creator, Dana Calvo]
-
A.
Dana Calvo
chosen
Dana Calvo is an American television writer and producer best known for creating the period drama series "Good Girls Revolt."
-
B.
Emily Cisneros
Emily Cisneros was the second wife of American character actor John Carradine, known primarily in relation to his life and career.
-
C.
Andrea Cantillo
Andrea Cantillo is a kind-hearted single mother and recovering addict who becomes Jesse Pinkman’s love interest in the television series "Breaking Bad."
-
D.
Liz Trujillo
Liz Trujillo is an American reality television personality best known for her relationship with rapper and TV star Flavor Flav, with whom she appeared on the series "Couples Therapy."
-
E.
Alexis Chávez
Alexis Chávez is an Argentine Paralympic middle-distance runner known for competing in international para-athletics events.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53344c6b081908e780ed5c815a766 |
completed | April 19, 2026, 7:55 p.m. |
Created at: April 10, 2026, 11:36 a.m.