Triple
T19912923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Is Hell |
E478592
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Wonderwall |
—
|
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: Wonderwall | Statement: [Love Is Hell, hasTrack, Wonderwall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonderwall Context triple: [Love Is Hell, hasTrack, Wonderwall]
-
A.
Wonderwall
chosen
"Wonderwall" is a 1995 Britpop anthem by the English rock band Oasis that became one of their most iconic and commercially successful songs worldwide.
-
B.
Somewhere
"Somewhere" is a track by the American rock band Soundgarden from their influential 1991 album *Badmotorfinger*.
-
C.
Somewhere
Somewhere is a 2010 introspective drama film written and directed by Sofia Coppola that follows a disaffected Hollywood actor reconnecting with his young daughter.
-
D.
Somewhere
"Somewhere" is a poignant ballad from the musical West Side Story that expresses a longing for a peaceful place where love can transcend conflict and prejudice.
-
E.
Somewhere
"Somewhere" is a stage play by American playwright Matthew López that explores themes of family, ambition, and the pursuit of dreams against the backdrop of mid-20th-century New York City.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659917fdc8190bf29bfdab0fe8f85 |
completed | April 20, 2026, 4:51 p.m. |
Created at: April 10, 2026, 1:53 p.m.