Triple
T3477146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SaveMoney |
E73400
|
entity |
| Predicate | notableMember |
P10
|
FINISHED |
| Object | Brian Fresco |
E404365
|
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: Brian Fresco | Statement: [SaveMoney, notableMember, Brian Fresco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Fresco Context triple: [SaveMoney, notableMember, Brian Fresco]
-
A.
Brian Fresco
chosen
Brian Fresco is a Chicago-based rapper known as a member of the SaveMoney collective alongside artists like Chance the Rapper and Vic Mensa.
-
B.
Greg Finton
Greg Finton is a film editor known for his work on documentaries and feature films, including the acclaimed documentary "He Named Me Malala."
-
C.
Ken Schretzmann
Ken Schretzmann is a film editor known for his work on major animated features, including Guillermo del Toro's stop-motion adaptation of Pinocchio.
-
D.
Mark Dacascos
Mark Dacascos is an American actor and martial artist known for his roles in action films and television, as well as for serving as the Chairman on the TV show "Iron Chef America."
-
E.
Andy Robustelli
Andy Robustelli was a Hall of Fame defensive end best known for his dominant play with the New York Giants during the 1950s and early 1960s.
- 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb5a5cb88190be5624ae224e4c91 |
completed | March 8, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c2144708190a4a620222eeee5d3 |
completed | March 14, 2026, 11:53 a.m. |
Created at: March 8, 2026, 3:17 p.m.