Triple
T22409477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endless Summer Vacation |
E553959
|
entity |
| Predicate | includesHitSingle |
P15293
|
FINISHED |
| Object | Flowers |
—
|
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: Flowers | Statement: [Endless Summer Vacation, includesHitSingle, Flowers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flowers Context triple: [Endless Summer Vacation, includesHitSingle, Flowers]
-
A.
Flowers
"Flowers" is a poignant song from the musical *Hadestown* that explores themes of love, loss, and memory through Eurydice’s perspective.
-
B.
Flowers
Flowers was the original name of the Australian rock band Icehouse, known for its new wave and synth-pop hits in the 1980s.
-
C.
Flowers
chosen
"Flowers" is a 2023 pop single by Miley Cyrus that became a global hit for its empowering lyrics about self-love and independence.
-
D.
Flowers
Flowers is a common English surname shared by various notable individuals across fields such as sports, music, and politics.
-
E.
Flowers
Flowers is a dark British comedy-drama television series that explores the dysfunctional lives of the eccentric Flowers family.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158bb9ef88190a773d82ac9ed7a55 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 16, 2026, 8:46 p.m.