Triple
T12905904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storm Front |
E308727
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | That's Not Her Style |
E1008571
|
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: That's Not Her Style | Statement: [Storm Front, hasSingle, That's Not Her Style]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: That's Not Her Style Context triple: [Storm Front, hasSingle, That's Not Her Style]
-
A.
That's Not Her Style
chosen
"That's Not Her Style" is a song by the American rock band Storm Front.
-
B.
She’s Not Me
"She’s Not Me" is a pop song by Swedish singer Tove Lo from her debut studio album "Queen of the Clouds."
-
C.
She’s Not Me
"She’s Not Me" is a song by Swedish singer-songwriter Lykke Li from her 2014 album *I Never Learn*, known for its melancholic tone and themes of heartbreak and emotional vulnerability.
-
D.
She’s Not for You
"She’s Not for You" is a country song by Willie Nelson featured on his 1973 album *Shotgun Willie*.
-
E.
She Wasn’t You
"She Wasn’t You" is a romantic ballad from the Burton Lane–Alan Jay Lerner stage musical *On a Clear Day You Can See Forever*.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971831bd48190b0ecd13e7181bbc6 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af5c133c81908b52fc18262c819d |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:41 p.m.