Triple
T1475268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille |
E30825
|
entity |
| Predicate | hasBSide |
P15273
|
FINISHED |
| Object | Till I Get It Right |
E96176
|
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: Till I Get It Right | Statement: [Lucille, hasBSide, Till I Get It Right]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Till I Get It Right Context triple: [Lucille, hasBSide, Till I Get It Right]
-
A.
Till I Get It Right
chosen
"Till I Get It Right" is a country song best known for Tammy Wynette’s 1972 hit recording, noted for its introspective lyrics about perseverance in love.
-
B.
You Got Me
"You Got Me" is a Grammy-winning neo-soul/hip-hop song by The Roots featuring Erykah Badu, widely recognized for its innovative blend of live instrumentation and introspective lyricism.
-
C.
Get It Back
"Get It Back" is a song by Whitney Houston featured on her 1998 album *My Love Is Your Love*.
-
D.
I Got a Right Ta
"I Got a Right Ta" is a song featured on the album "Electric Circus" by rapper and producer Common.
-
E.
Come and Get It
Come and Get It is a 1936 American drama film, co-directed by Howard Hawks and William Wyler, best known for featuring Walter Brennan in an Oscar-winning supporting performance.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c602387c8190b97a20c8e05e3d16 |
completed | March 1, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15ab9430819094deb90436983036 |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 8:11 p.m.