Triple
T20107949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do You Love Her |
E490245
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Do You Love Her |
—
|
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: Do You Love Her | Statement: [Do You Love Her, name, Do You Love Her]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Do You Love Her Context triple: [Do You Love Her, name, Do You Love Her]
-
A.
Do You Love Her
chosen
"Do You Love Her" is a song featured on the album "Romance Dance" by Kim Carnes.
-
B.
Do You Love Her Now
"Do You Love Her Now" is a critically acclaimed R&B/electronic track by elusive British musician Jai Paul, known for its hazy production, emotive vocals, and long-anticipated official release after years of cult fandom.
-
C.
I Love Her
"I Love Her" is a song by Ray Ray, known for its smooth R&B style and romantic lyrics.
-
D.
Ma, I Don't Love Her
"Ma, I Don't Love Her" is a hip-hop track by the duo Clipse, known for its storytelling about complicated relationships over a Neptunes-produced beat.
-
E.
Tell Her You Love Her
"Tell Her You Love Her" is a work of fiction by British writer Bridget O’Connor, known for her sharp, darkly comic storytelling.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666ddb09881909ad2aedd1e8a78da |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:28 p.m.