Triple
T13384656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Retta |
E319407
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Good Girls |
E319400
|
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: Good Girls | Statement: [Retta, notableWork, Good Girls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Good Girls Context triple: [Retta, notableWork, Good Girls]
-
A.
Good Girls
chosen
Good Girls is an American dark comedy-drama television series about three suburban mothers who turn to crime to solve their financial problems.
-
B.
Good Girls
"Good Girls" is a pop-rock song by Australian band 5 Seconds of Summer, known for its catchy hooks and themes of defying good-girl stereotypes.
-
C.
Very Good Girls
Very Good Girls is a 2013 coming-of-age drama film about two best friends whose bond is tested when they fall for the same young man.
-
D.
Good Girls, Bad Guys
"Good Girls, Bad Guys" is a hip-hop track by DMX from his 1999 album "...And Then There Was X."
-
E.
Goodtime Girls
Goodtime Girls is an early-1980s American sitcom that followed the comedic misadventures of young women sharing an apartment during World War II.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce80158819082156eaeaeda3bd8 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7268cf04c8190a35fd48ce81c149e |
completed | May 3, 2026, 10:42 a.m. |
Created at: April 9, 2026, 9:33 p.m.