Triple
T17887083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvester Pemberton |
E447224
|
entity |
| Predicate | partner |
P1136
|
FINISHED |
| Object | Stripesy |
—
|
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: Stripesy | Statement: [Sylvester Pemberton, partner, Stripesy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stripesy Context triple: [Sylvester Pemberton, partner, Stripesy]
-
A.
Stripesy
chosen
Stripesy is a Golden Age DC Comics superhero, better known as Pat Dugan, who fights crime in a patriotic costume and later becomes the armored hero S.T.R.I.P.E.
-
B.
Tune Squad
Tune Squad is the fictional basketball team of Looney Tunes characters that competes alongside Michael Jordan in the 1996 film "Space Jam."
-
C.
Odeo
Odeo was an early podcasting startup co-founded by the team behind Obvious Corporation that played a key role in the creation of Twitter.
-
D.
Harmonize
Harmonize is a Tanzanian singer and songwriter known for his Bongo Flava hits and for helping popularize East African music across the continent.
-
E.
Trixter
Trixter is an American hard rock band best known for their early 1990s glam metal hits and MTV presence.
- 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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c14c4348190bb77712d9eae1d51 |
completed | April 19, 2026, 9:10 a.m. |
Created at: April 10, 2026, 10:18 a.m.