Triple
T10008016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sad Songs for Dirty Lovers |
E198300
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lucky You |
E588076
|
NE FINISHED |
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: Lucky You | Statement: [Sad Songs for Dirty Lovers, hasPart, Lucky You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucky You Context triple: [Sad Songs for Dirty Lovers, hasPart, Lucky You]
-
A.
Lucky You
chosen
Lucky You is a 2007 romantic drama film set in the high-stakes world of professional poker in Las Vegas, starring Eric Bana and Drew Barrymore.
-
B.
Lucky Me
"Lucky Me" is a 1954 Technicolor musical comedy film starring Doris Day as a superstitious chorus girl who finds romance and career opportunities in Miami.
-
C.
Lucky Me
"Lucky Me" is a track featured on Big Sean's 2020 hip-hop album "Detroit 2."
-
D.
The Luckiest
"The Luckiest" is a tender piano ballad by singer-songwriter Ben Folds, celebrated for its heartfelt lyrics about love, fate, and lifelong companionship.
-
E.
Lucky Day
Lucky Day is one of the three bumbling silent-film actors who mistakenly become real-life heroes in the comedy film "Three Amigos."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd187fe481908556ea896c528ea4 |
completed | April 2, 2026, 1:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d28209678c8190898d923753bb4472 |
completed | April 5, 2026, 3:38 p.m. |
Created at: March 30, 2026, 8:52 p.m.