Triple
T20408269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Sux |
E500525
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Head Above Water |
—
|
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: Head Above Water | Statement: [Love Sux, follows, Head Above Water]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Head Above Water Context triple: [Love Sux, follows, Head Above Water]
-
A.
Head Above Water
chosen
"Head Above Water" is a 2018 pop-rock ballad by Canadian singer Avril Lavigne that marked her comeback after a long battle with Lyme disease.
-
B.
High Water Everywhere
"High Water Everywhere" is a seminal 1929 Delta blues song by Charley Patton that vividly chronicles the devastation of the Great Mississippi Flood.
-
C.
Treading Water
"Treading Water" is a song by the American rock band Hope.
-
D.
Deep Water
"Deep Water" is a soulful, introspective song by British singer Seal from his self-titled debut album, blending atmospheric production with emotive vocals.
-
E.
Deep Water
Deep Water is a psychological thriller novel by Patricia Highsmith that explores the dark undercurrents of a seemingly ordinary marriage and the murderous impulses lurking beneath.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3d03ac81908f37b907ccbb5088 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.