Triple
T20436357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treat Myself |
E501259
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Wave |
—
|
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: Wave | Statement: [Treat Myself, hasPart, Wave]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wave Context triple: [Treat Myself, hasPart, Wave]
-
A.
Wave
Wave is a 1979 studio album by American musician Patti Smith that blends punk, rock, and poetic lyricism and marked her last release before a long hiatus from recording.
-
B.
Wave
chosen
"Wave" is a critically acclaimed song by Canadian singer-songwriter Patrick Watson, known for its haunting vocals, cinematic arrangement, and emotional lyricism.
-
C.
Wave
Wave is a 1967 bossa nova jazz album by Brazilian composer Antônio Carlos Jobim, renowned for its lush orchestral arrangements and the classic title track.
-
D.
Waves
"Waves" is a melodic, gospel-influenced hip-hop song by Kanye West featuring Chris Brown and Kid Cudi, known for its soaring chorus and spiritual themes.
-
E.
Waves
"Waves" is a smooth, atmospheric R&B song by Miguel that showcases his sensual vocals and genre-blending production.
- 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_69e0b4ab3cfc8190ac9bf32e932316b1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e685ef5fc8819089e3f97a63a52f86 |
completed | April 20, 2026, 8 p.m. |
Created at: April 16, 2026, 11:31 a.m.