Triple
T20668137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathryn Grayson |
E507945
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Lovely to Look At |
—
|
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: Lovely to Look At | Statement: [Kathryn Grayson, notableWork, Lovely to Look At]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lovely to Look At Context triple: [Kathryn Grayson, notableWork, Lovely to Look At]
-
A.
Lovely to Look At
chosen
Lovely to Look At is a 1952 MGM musical film, loosely based on the stage musical Roberta, featuring lavish Technicolor production numbers and classic Jerome Kern songs.
-
B.
So Lovely
"So Lovely" is a song featured on the album *To Whom It May Concern*.
-
C.
Lovelier Than You
"Lovelier Than You" is a melodic pop-rap love song by American rapper B.o.B from his debut studio album.
-
D.
Lovely Lady
Lovely Lady is a fragrance from the Made in Brooklyn collection, known for its feminine, urban-inspired scent profile.
-
E.
Sweet and Lovely
"Sweet and Lovely" is a popular jazz and pop standard from the early 1930s that has been widely recorded by numerous vocalists and instrumentalists.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c4c4608190ae17da4a59e5ae80 |
completed | April 20, 2026, 11:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.