Triple
T16679506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cause and Effect |
E405301
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | Love Too Much |
E1228177
|
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 Too Much | Statement: [Cause and Effect, hasSingle, Love Too Much]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Too Much Context triple: [Cause and Effect, hasSingle, Love Too Much]
-
A.
Love Too Much
chosen
Love Too Much is a song by British singer-songwriter Keane from their 2019 album "Cause and Effect."
-
B.
Love You Too Much
"Love You Too Much" is a song by the American rock band Painted.
-
C.
I Love You Too Much
"I Love You Too Much" is a song by Stevie Wonder featured on his 1985 album *In Square Circle*.
-
D.
Never Too Much
"Never Too Much" is a 1981 R&B and soul classic by Luther Vandross that became his signature hit and a defining song of contemporary R&B.
-
E.
Too Much
"Too Much" is a reflective, emotionally charged song by Canadian rapper Drake that appears on his 2013 album *Nothing Was the Same*.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6e74ec81909ea95c3e4b0113ab |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009194ad188190aae3371c97abc045 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.