Triple
T13725958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purple Naked Ladies |
E329653
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | They Say |
E67289
|
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: They Say | Statement: [Purple Naked Ladies, hasPart, They Say]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: They Say Context triple: [Purple Naked Ladies, hasPart, They Say]
-
A.
They Say
chosen
"They Say" is a song title that has been used by multiple artists across genres, typically exploring themes of external judgment and personal identity.
-
B.
Say It
"Say It" is a track by the American hip hop group R.E.D, featured as part of their musical releases.
-
C.
Say It
"Say It" is a song by American alternative rock band Blue October, known for its emotionally charged lyrics and intense, melodic sound.
-
D.
Say It
"Say It" is a track by Rihanna from her acclaimed 2007 album *Good Girl Gone Bad*, blending R&B and pop influences with sensual, confessional lyrics.
-
E.
She Said
"She Said" is a 2022 drama film that chronicles The New York Times investigation into Harvey Weinstein’s sexual misconduct, helping to ignite the #MeToo movement.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f63c1c8190a7d0b84f319aa99b |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d60cd048190b20c4e6f49f816a6 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:55 p.m.