Triple
T22745099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Pullen |
E562527
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jacob Pullen |
—
|
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: Jacob Pullen | Statement: [Jacob Pullen, name, Jacob Pullen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jacob Pullen Context triple: [Jacob Pullen, name, Jacob Pullen]
-
A.
Jacob Pullen
chosen
Jacob Pullen is an American professional basketball player best known as a high-scoring, clutch guard and all-time leading scorer during his standout collegiate career at Kansas State University.
-
B.
Luke Bullen
Luke Bullen is an English drummer and percussionist best known for his work as a touring and session musician with prominent rock and pop acts.
-
C.
Jeff Nathanson
Jeff Nathanson is an American screenwriter and film director best known for writing high-profile Hollywood films such as "Catch Me If You Can," "The Terminal," and Disney's live-action "The Lion King."
-
D.
Keith Poulson
Keith Poulson is an American actor known for his work in independent films and for roles in offbeat, character-driven movies.
-
E.
Jon Plowman
Jon Plowman is a British television producer best known for his influential work on BBC comedies, including series such as Absolutely Fabulous and The Office.
- 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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b563e481908804d07fca1777b9 |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:23 p.m.