Triple
T16695412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaDonna Adrian Gaines |
E405702
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Bad Girls |
E163940
|
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: Bad Girls | Statement: [LaDonna Adrian Gaines, notableWork, Bad Girls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Girls Context triple: [LaDonna Adrian Gaines, notableWork, Bad Girls]
-
A.
Bad Girls
chosen
"Bad Girls" is a 1979 disco hit album by Donna Summer, widely regarded as one of her signature works and a landmark of the disco era.
-
B.
Bad Girls
"Bad Girls" is a 1994 American Western film about four former prostitutes on the run, produced and co-written by Lynda Obst.
-
C.
Bad Girls
"Bad Girls" is a 2012 single by British-Sri Lankan artist M.I.A., known for its Middle Eastern–influenced production and a visually striking, stunt-filled music video that critiques gender norms and driving bans.
-
D.
Bad Girl
"Bad Girl" is a high-energy R&B/pop single by Danity Kane known for its club-ready production and confident, empowering lyrics.
-
E.
Bad Girl
"Bad Girl" is a track from the album "Erotica," known for its provocative themes and sensual style.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37eacfa788190a8d2058f96c0d445 |
completed | April 18, 2026, 12:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00919acd308190a3f29040554b9cfc |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.