Triple
T19913814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 18 til I Die |
E478612
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Star |
—
|
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: Star | Statement: [18 til I Die, hasTrack, Star]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Star Context triple: [18 til I Die, hasTrack, Star]
-
A.
Star
Star was an automobile marque produced by Durant Motors in the 1920s as a lower-priced competitor to brands like Ford and Chevrolet.
-
B.
Star
Star is the costumed mascot character for the WNBA’s Atlanta Dream, entertaining fans and representing the team at games and events.
-
C.
Star
chosen
"Star" is a musical drama television series created by Lee Daniels and Tom Donaghy that follows three talented young singers navigating the challenges of the music industry in Atlanta.
-
D.
Star
Star is a small but growing suburban city in southwestern Idaho that forms part of the Boise metropolitan area.
-
E.
Star
Star is the surname of American television producer, director, and writer Darren Star, best known for creating hit series such as "Sex and the City" and "Beverly Hills, 90210."
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659928030819085a4aafc6a0ef5c8 |
completed | April 20, 2026, 4:51 p.m. |
Created at: April 10, 2026, 1:53 p.m.