Triple
T3783117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robyn Rihanna Fenty |
E85464
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Good Girl Gone Bad |
E87100
|
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 Girl Gone Bad | Statement: [Robyn Rihanna Fenty, notableWork, Good Girl Gone Bad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Good Girl Gone Bad Context triple: [Robyn Rihanna Fenty, notableWork, Good Girl Gone Bad]
-
A.
Good Girl Gone Bad
chosen
Good Girl Gone Bad is Rihanna's critically acclaimed 2007 pop and R&B album that marked her transition to a more edgy, mature image and sound.
-
B.
Good Girl
"Good Girl" is an uptempo country-pop song by Carrie Underwood that warns a woman about an untrustworthy lover, showcasing her powerful vocals and crossover appeal.
-
C.
Naughty Girl
"Naughty Girl" is a hit R&B song by Beyoncé from her debut solo album, noted for its sultry vocals and Middle Eastern–influenced production.
-
D.
Your Girl
"Your Girl" is a song by Mariah Carey from her 2005 album *The Emancipation of Mimi*.
-
E.
Bad Girls
"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.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee3db11108190aa81ee8ed22709fe |
completed | March 9, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f04747448190be484cda5b2a7a8c |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:13 p.m.