Triple
T13722522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fruit at the Bottom |
E329071
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Lolly Lolly |
E1055353
|
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: Lolly Lolly | Statement: [Fruit at the Bottom, hasTrack, Lolly Lolly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lolly Lolly Context triple: [Fruit at the Bottom, hasTrack, Lolly Lolly]
-
A.
Lolly Lolly
chosen
"Lolly Lolly" is a funk-infused pop song by the duo Wendy & Lisa, known for its catchy groove and late-1980s production style.
-
B.
Lolly
Lolly is a diminutive or affectionate nickname commonly used for the given name Laura.
-
C.
Lollipop
"Lollipop" is a 2008 hit hip-hop single by Lil Wayne that became one of his most commercially successful and culturally influential songs.
-
D.
Lola Lola
Lola Lola is the seductive cabaret singer portrayed by Marlene Dietrich in the classic 1930 German film "The Blue Angel."
-
E.
La-La-La
"La-La-La" is a musical composition by renowned American composer Richard Rodgers, best known for his influential contributions to 20th-century musical theatre.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f3b46481909ceedfa78e9ca92b |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d5e1ecc8190a9fec550a99702c0 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:55 p.m.