Triple
T23444772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skeet Ulrich |
E565504
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Skeet |
—
|
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: Skeet | Statement: [Skeet Ulrich, hasGivenName, Skeet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skeet Context triple: [Skeet Ulrich, hasGivenName, Skeet]
-
A.
Skeet
chosen
Skeet is a music producer known for contributing to hip-hop projects such as De La Soul’s influential album "Stakes Is High."
-
B.
Zielschuss
Zielschuss is the famously steep and high-speed final section of Kitzbühel’s Hahnenkamm downhill ski race course, where racers reach some of their highest velocities before the finish.
-
C.
Bullseye
Bullseye is Woody’s loyal toy horse in the Toy Story franchise, known for his expressive, nonverbal personality and close bond with the other toys.
-
D.
Bullseye
"Bullseye" is a thriller novel in James Patterson and Michael Ledwidge's Michael Bennett series, following the NYPD detective as he races to stop an assassination plot against the U.S. president.
-
E.
Bullseye
Bullseye is a British television game show that combines darts with general knowledge quizzes, originally popular in the 1980s and 1990s.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a647d6208190ba891252c8443fd4 |
completed | April 29, 2026, 6:33 a.m. |
Created at: April 17, 2026, 5:51 p.m.