Triple
T19234509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sea of Memories |
E480958
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | I Believe in You |
—
|
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 Believe in You | Statement: [The Sea of Memories, hasTrack, I Believe in You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Believe in You Context triple: [The Sea of Memories, hasTrack, I Believe in You]
-
A.
I Believe in You
"I Believe in You" is a track by Snoop Dogg from his 2002 studio album "Paid tha Cost to Be da Boss."
-
B.
I Believe in You
"I Believe in You" is a popular song from the 1961 Broadway musical *How to Succeed in Business Without Really Trying*, composed by Frank Loesser.
-
C.
I Believe in You
chosen
"I Believe in You" is a reflective, piano-driven song by Neil Young known for its introspective lyrics and gentle, melancholic tone.
-
D.
I Believe in You and Me
"I Believe in You and Me" is a romantic ballad best known for Whitney Houston’s powerful rendition, featured on the soundtrack of the film *The Preacher’s Wife*.
-
E.
I Still Believe in You
"I Still Believe in You" is a hit country song and album by Vince Gill that became one of his signature works in the early 1990s.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faeb53988190b83afee9974058c6 |
completed | April 20, 2026, 10:07 a.m. |
Created at: April 10, 2026, 1:26 p.m.