Triple
T16753041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Take a Bow |
E407131
|
entity |
| Predicate | followsSingle |
P9710
|
FINISHED |
| Object | Hate That I Love You |
E404296
|
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: Hate That I Love You | Statement: [Take a Bow, followsSingle, Hate That I Love You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hate That I Love You Context triple: [Take a Bow, followsSingle, Hate That I Love You]
-
A.
Hate That I Love You
chosen
"Hate That I Love You" is a mid-tempo R&B-pop duet by Rihanna featuring Ne-Yo that explores the emotional conflict of loving someone despite their flaws.
-
B.
I Hate Love
"I Hate Love" is a song written by American songwriter and producer Claude Kelly, known for his work with major pop and R&B artists.
-
C.
Love to Hate You
"Love to Hate You" is a 1991 synth-pop song by the British duo Erasure, known for its catchy melody and playful lyrics about a love–hate romantic relationship.
-
D.
Hate My Love
"Hate My Love" is a song featured in the stage musical adaptation of The Proclaimers' music, Sunshine on Leith.
-
E.
I Hate You
"I Hate You" is a song featured on the album *Back into Your System* by the American rock band Saliva.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa28fd3c8190972e2e69ea7dece0 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52402848190b029cb0be31b4c74 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.