Triple
T15594940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Know That I Love You |
E374866
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | To Know That I Love You |
E374866
|
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: To Know That I Love You | Statement: [To Know That I Love You, hasTitle, To Know That I Love You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: To Know That I Love You Context triple: [To Know That I Love You, hasTitle, To Know That I Love You]
-
A.
To Know That I Love You
chosen
"To Know That I Love You" is a song by the American rock band Simple Plan from their album "Simple Things."
-
B.
I Know About Love
"I Know About Love" is a song from the classic Rodgers and Hammerstein musical "Do Re Mi."
-
C.
But You Know I Love You
"But You Know I Love You" is a country-pop song best known for its hit recording by Kenny Rogers and The First Edition in the late 1960s.
-
D.
Why I Love You
"Why I Love You" is a song by Jay-Z and Kanye West from their collaborative album *Watch the Throne*, known for its dramatic production and themes of loyalty and betrayal.
-
E.
How You Love Me
"How You Love Me" is a song by American rapper Talib Kweli from his album *Gutter Rainbows*.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5f9db8819083abf80f01f32b3d |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56c7db58819089cb488fb3ea96cd |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:12 a.m.