Triple
T20386293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funny About Love |
E497964
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Funny About Love |
—
|
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: Funny About Love | Statement: [Funny About Love, title, Funny About Love]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Funny About Love Context triple: [Funny About Love, title, Funny About Love]
-
A.
Funny About Love
chosen
Funny About Love is a 1990 romantic comedy film starring Gene Wilder that explores the complications of love, marriage, and the desire to have children.
-
B.
Love Is a Funny Thing
"Love Is a Funny Thing" is a song featured on the album *Weather or Not* by rapper and producer Evidence.
-
C.
Love 4 Fun
"Love 4 Fun" is a song featured on the album *Escape* by the Eurodance group E-Rotic.
-
D.
Love, Laughter and Tears
Love, Laughter and Tears is a memoir by American journalist and author Adela Rogers St. Johns, reflecting on her life, career, and the emotional experiences that shaped her.
-
E.
Love, Inc.
Love, Inc. is an American television sitcom that follows a group of dating consultants as they help clients find love while navigating their own romantic lives.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790bcef481909453d19c846ab420 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.