Triple
T23546553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Beyincé |
E577910
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Pray You Catch Me |
—
|
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: Pray You Catch Me | Statement: [Angela Beyincé, notableWork, Pray You Catch Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pray You Catch Me Context triple: [Angela Beyincé, notableWork, Pray You Catch Me]
-
A.
Pray You Catch Me
chosen
"Pray You Catch Me" is the atmospheric, emotionally raw opening track of Beyoncé's visual album *Lemonade*, setting the tone with themes of suspicion, betrayal, and vulnerability.
-
B.
I'll Catch You
"I'll Catch You" is an emotional indie rock ballad by The Get Up Kids, known as a fan-favorite closer from their influential early-2000s album "Something to Write Home About."
-
C.
You Have Caught Me
"You Have Caught Me" is a reggae song by Jamaican vocal trio The Melodians, known for its smooth harmonies and classic rocksteady-influenced style.
-
D.
Pray for Me
"Pray for Me" is a track by Snoop Dogg featured on his album "Doggumentary."
-
E.
Pray for Me
"Pray for Me" is an R&B/soul song by American singer Anthony Hamilton, known for its heartfelt lyrics and gospel-infused sound.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aecb567c8190a54d2c3b63282af5 |
completed | April 29, 2026, 7:10 a.m. |
Created at: April 17, 2026, 6:11 p.m.