Triple
T2079327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loscutoff |
E45201
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Jim Loscutoff |
E7534
|
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: Jim Loscutoff | Statement: [Loscutoff, usedBy, Jim Loscutoff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Loscutoff Context triple: [Loscutoff, usedBy, Jim Loscutoff]
-
A.
Jim Loscutoff
chosen
Jim Loscutoff was an American professional basketball forward best known for his rugged defense and seven NBA championships with the Boston Celtics in the 1950s and 1960s.
-
B.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
C.
Tom Lofaro
Tom Lofaro is a television producer best known for his executive production work on the long-running comedy series "It's Always Sunny in Philadelphia."
-
D.
Brian Bilello
Brian Bilello is an American soccer executive best known for leading Major League Soccer’s New England Revolution as the club’s president.
-
E.
Craig Bierko
Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
- 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba3307308190ab329fe3192b2e0f |
completed | March 7, 2026, 5:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae3056aa0c8190b19d97ac0c3bc31d |
completed | March 9, 2026, 2:28 a.m. |
Created at: March 4, 2026, 7:41 p.m.