Triple
T13747316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angel Lopez |
E330246
|
entity |
| Predicate | workOn |
P30363
|
FINISHED |
| Object | "Every Hour" |
E1060363
|
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: "Every Hour" | Statement: [Angel Lopez, workOn, "Every Hour"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: "Every Hour" Context triple: [Angel Lopez, workOn, "Every Hour"]
-
A.
"Every Hour"
chosen
"Every Hour" is a song best known as a gospel-influenced track associated with artist and producer Angel Lopez.
-
B.
Every Hour
"Every Hour" is a gospel-infused opening track by Kanye West featuring the Sunday Service Choir from his 2019 album *Jesus Is King*.
-
C.
On the Hour
On the Hour is a British satirical radio news programme that parodies current affairs broadcasting with surreal and darkly comic sketches.
-
D.
Ev’ry Night at Seven
"Ev’ry Night at Seven" is a romantic show tune from the Burton Lane–Alan Jay Lerner stage musical *On a Clear Day You Can See Forever*.
-
E.
"Hrs & Hrs"
"Hrs & Hrs" is a viral R&B love ballad by Muni Long that gained widespread popularity for its intimate lyrics and soulful, melodic delivery.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02132a108190aca728b95e83af01 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b06d9fd48190a10b86a0d68fac70 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:08 p.m.