Triple
T18234071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love and Learn |
E436621
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Love and Learn |
—
|
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: Love and Learn | Statement: [Love and Learn, hasTitle, Love and Learn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love and Learn Context triple: [Love and Learn, hasTitle, Love and Learn]
-
A.
Love and Learn
chosen
Love and Learn is a 1947 American romantic comedy film produced by Warner Bros.
-
B.
The Love School
The Love School is a British television drama series in which Ben Kingsley starred, exploring the lives and relationships of the Pre-Raphaelite artists.
-
C.
Lessons in Love
"Lessons in Love" is a 1986 pop song by the British band Level 42, featuring Mark King’s distinctive bass playing and becoming one of their biggest international hits.
-
D.
The Pursuit of Love
The Pursuit of Love is a British television adaptation of Nancy Mitford’s classic novel, following the romantic and social misadventures of an eccentric upper-class English family between the World Wars.
-
E.
Ready for Love
"Ready for Love" is a song best known as a soulful rock ballad popularized by the band Bad Company.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b512a88190aa493b0793ab28b3 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 10, 2026, 10:33 a.m.