Triple
T9629263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Gould |
E232553
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Joe Gould |
E164464
|
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: Joe Gould | Statement: [Jason Gould, hasRelative, Joe Gould]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Gould Context triple: [Jason Gould, hasRelative, Joe Gould]
-
A.
Joe Gould
chosen
Joe Gould was the real-life boxing manager best known for guiding heavyweight champion James J. Braddock during his improbable rise in the 1930s.
-
B.
Irving Gordon
Irving Gordon was an American songwriter best known for penning enduring standards such as "Unforgettable" and other popular mid-20th-century ballads.
-
C.
Charles Guggenheim
Charles Guggenheim was an American documentary filmmaker renowned for his politically engaged and historically focused films, earning multiple Academy Awards over his career.
-
D.
Fritz Lanman
Fritz Lanman is an American technology executive and investor known for his leadership roles at companies like ClassPass and his early investment in and involvement with startups such as Square.
-
E.
Erle C. Kenton
Erle C. Kenton was an American film director best known for his work on early horror and comedy films during Hollywood’s studio era.
- 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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b00162481908f396f6b6e470d6c |
completed | April 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d17987e4008190a8d43641072a1c86 |
completed | April 4, 2026, 8:50 p.m. |
Created at: March 30, 2026, 8:10 p.m.