Triple
T20519047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimme Gimme Shock Treatment |
E503755
|
entity |
| Predicate | isPrecededBy |
P97
|
FINISHED |
| Object | Glad to See You Go |
—
|
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: Glad to See You Go | Statement: [Gimme Gimme Shock Treatment, isPrecededBy, Glad to See You Go]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glad to See You Go Context triple: [Gimme Gimme Shock Treatment, isPrecededBy, Glad to See You Go]
-
A.
Glad to See You Go
chosen
"Glad to See You Go" is a punk rock song by the Ramones, known for its fast tempo and breakup-themed lyrics.
-
B.
Hate to See You Go
"Hate to See You Go" is a blues song famously covered by The Rolling Stones on their album *Blue & Lonesome*, originally recorded by Chicago blues musician Little Walter.
-
C.
When You Go
"When You Go" is a song featured on the album "To Whom It May Concern."
-
D.
This Ain’t Goodbye
"This Ain’t Goodbye" is a song by the American rock band Train from their album "Save Me, San Francisco."
-
E.
Good Goodbye
"Good Goodbye" is a pop ballad performed by American Idol alumna Diana DeGarmo, showcasing her powerful vocals and emotional delivery.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f44b6ac8190a4f2f5244821c433 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.