Triple
T21010578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pleasure & Pain |
E517536
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Love Me |
E517530
|
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: Love Me | Statement: [Pleasure & Pain, hasPart, Love Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Me Context triple: [Pleasure & Pain, hasPart, Love Me]
-
A.
Love Me
chosen
"Love Me" is a creative work, likely a song or film, recognized as a notable part of an artist's or creator's body of work.
-
B.
You Love Me
"You Love Me" is a pop song produced by Jesse Shatkin, known for its polished production and emotionally charged, radio-friendly sound.
-
C.
Let Me Love You
"Let Me Love You" is a mid-tempo R&B-influenced pop song by Ariana Grande featuring rapper Lil Wayne from her album *Dangerous Woman*.
-
D.
Let Me Love You
"Let Me Love You" is a 2004 R&B ballad by American singer Mario that became a major international hit and one of his signature songs.
-
E.
Let Me Love You
"Let Me Love You" is a 2016 EDM-pop song by DJ Snake featuring Justin Bieber that became a global hit for its catchy melody and emotional lyrics.
- 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc3fdf3c8190abd3db7f5eb503a0 |
completed | April 21, 2026, 4:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09473c3fa88190b6ca4dfbc7c1c409 |
completed | May 17, 2026, 4:42 a.m. |
Created at: April 16, 2026, 1:53 p.m.