Triple
T10306521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Fisk |
E241775
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Frank Fisk |
E241775
|
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: Frank Fisk | Statement: [Frank Fisk, name, Frank Fisk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Fisk Context triple: [Frank Fisk, name, Frank Fisk]
-
A.
Frank Fisk
chosen
Frank Fisk is an individual notable enough to be recognized as a bearer of the surname Fisk.
-
B.
William Fagan
William Fagan is a relatively obscure individual whose name is notably recorded as a bearer of the surname Fagan.
-
C.
Larry Foust
Larry Foust was an American professional basketball center and eight-time NBA All-Star who played primarily for the Fort Wayne Pistons in the 1950s.
-
D.
Thomas Fry
Thomas Fry is a personal name shared by multiple individuals, including various historical and contemporary figures across different professions.
-
E.
Ron Funches
Ron Funches is an American stand-up comedian and actor known for his warm, laid-back delivery and distinctive voice work in animated films and television.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d30a6c888190acdd0a645247736a |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d794ddbd9081909a534b29b3f75774 |
completed | April 9, 2026, noon |
Created at: April 6, 2026, 11:46 a.m.