Triple
T20311661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Send Me the Pillow |
E510264
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Send Me the Pillow |
—
|
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: Send Me the Pillow | Statement: [Send Me the Pillow, hasTitle, Send Me the Pillow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Send Me the Pillow Context triple: [Send Me the Pillow, hasTitle, Send Me the Pillow]
-
A.
Send Me the Pillow
chosen
"Send Me the Pillow" is a classic country song best known through numerous recordings, including a popular version by Hank Locklin.
-
B.
Helmet for My Pillow
Helmet for My Pillow is a World War II memoir by U.S. Marine Robert Leckie recounting his combat experiences in the Pacific theater.
-
C.
Love on a Pillow
Love on a Pillow is a 1962 French romantic drama film starring Brigitte Bardot as a young woman drawn into a destructive relationship after saving a stranger’s life.
-
D.
Send for Me
"Send for Me" is a song featured on the album "First Two Pages of Frankenstein" by The National.
-
E.
Send Me the Moon
"Send Me the Moon" is a gentle, piano-driven ballad by Sara Bareilles featured on her album "Kaleidoscope Heart."
- 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e677441f9c8190acf98dc92c77732b |
completed | April 20, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:19 a.m.