Triple
T20618495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Want to Be on TV |
E506632
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | I Want to Be on TV |
—
|
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: I Want to Be on TV | Statement: [I Want to Be on TV, title, I Want to Be on TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Want to Be on TV Context triple: [I Want to Be on TV, title, I Want to Be on TV]
-
A.
I Want to Be on TV
"I Want to Be on TV" is a punk rock song by Green Day, released as the B-side to their single "Geek Stink Breath."
-
B.
I Want to Be on TV
chosen
"I Want to Be on TV" is a punk rock song by the band Shenanigans, known for its energetic style and satirical take on fame and media culture.
-
C.
I Should Watch TV
"I Should Watch TV" is a song by the experimental rock duo David Byrne and St. Vincent from their collaborative album "Love This Giant."
-
D.
I Want to Be Happy
"I Want to Be Happy" is a jazz standard from the 1925 musical "No, No, Nanette," widely performed and recorded by numerous jazz artists.
-
E.
I Want To Be Me
"I Want To Be Me" is a short film featuring actress Miracle Laurie that explores themes of identity and self-acceptance.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abdf9d7c8190969247a4ae55b781 |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:41 a.m.