Triple
T19504990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | But I'm a Cheerleader |
E487998
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | RuPaul Charles |
—
|
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: RuPaul Charles | Statement: [But I'm a Cheerleader, stars, RuPaul Charles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RuPaul Charles Context triple: [But I'm a Cheerleader, stars, RuPaul Charles]
-
A.
RuPaul Charles
chosen
RuPaul Charles is an American drag queen, television host, producer, and pop culture icon best known for creating and hosting the reality competition series "RuPaul's Drag Race."
-
B.
Chaz Bono
Chaz Bono is an American writer, musician, and LGBTQ+ advocate best known as a prominent transgender activist and the only child of entertainers Cher and Sonny Bono.
-
C.
David Chytraeus
David Chytraeus was a 16th-century German Lutheran theologian and reformer, known as one of the key contributors to the development and consolidation of Lutheran confessional documents.
-
D.
Hue Hef
Hue Hef is a hip-hop artist known for his guest appearance on the track "The Meth Lab."
-
E.
Greg Serano
Greg Serano is an American actor known for his supporting roles in film and television, including appearances in projects like "Deadly Impact," "Legally Blonde," and the series "Power."
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.