Triple
T17180868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phil Foster |
E416977
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Phil Foster |
—
|
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: Phil Foster | Statement: [Phil Foster, name, Phil Foster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phil Foster Context triple: [Phil Foster, name, Phil Foster]
-
A.
Phil Foster
chosen
Phil Foster was an American actor and comedian best known for playing Laverne’s father, Frank DeFazio, on the sitcom "Laverne & Shirley."
-
B.
Phil Foster
Phil Foster is the hapless yet determined suburban husband and father portrayed by Steve Carell in the comedy film "Date Night."
-
C.
Jim Foster
Jim Foster is an American sports executive best known as the creator and founding figure of the Arena Football League.
-
D.
Jeff Foster
Jeff Foster is an entrepreneur best known for founding the global athletic footwear and apparel brand Reebok.
-
E.
James Foster
James Foster is an economist known for his influential work on poverty measurement and social welfare, including co-developing the widely used Foster-Greer-Thorbecke (FGT) poverty indices.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc1187808190aeaa0d0e6487957e |
completed | April 18, 2026, 9:48 p.m. |
Created at: April 10, 2026, 5:37 a.m.