Triple
T16069949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballin' |
E389833
|
entity |
| Predicate | includedIn |
P1393
|
FINISHED |
| Object | Perfect Ten |
E1192925
|
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: Perfect Ten | Statement: [Ballin', includedIn, Perfect Ten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perfect Ten Context triple: [Ballin', includedIn, Perfect Ten]
-
A.
Perfect Ten
chosen
Perfect Ten is a hip-hop album best known for its polished production and collaborations with prominent rap artists.
-
B.
The Perfect 10
The Perfect 10 is an album by the artist Hello Friday, showcasing their polished pop sound and songwriting style.
-
C.
The Perfect Score
The Perfect Score is a 2004 teen heist comedy film about a group of high school students who plot to steal the answers to the SAT exam.
-
D.
Eleven on Top
Eleven on Top is a comedic crime novel in Janet Evanovich’s popular Stephanie Plum series, following the inept yet determined bounty hunter as she attempts to leave her job but is drawn back into danger and chaos.
-
E.
One in Ten
"One in Ten" is a politically charged reggae song by British band UB40 that highlights unemployment and social inequality in early 1980s Britain.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183bd9578819097e7cb1108b1f6f7 |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb8f12708190956f203a3e58e18b |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 4:57 a.m.