Triple
T21954212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeep Swenson |
E542143
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Swenson |
—
|
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: Swenson | Statement: [Jeep Swenson, familyName, Swenson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swenson Context triple: [Jeep Swenson, familyName, Swenson]
-
A.
Swenson
chosen
Swenson is a surname most notably associated with American stage and screen actor Will Swenson.
-
B.
Swanberg
Swanberg is a surname most notably associated with American independent filmmaker and actor Joe Swanberg, a key figure in the mumblecore movement.
-
C.
Sievers
Sievers is a German-language surname borne by various notable individuals across fields such as science, sports, and the arts.
-
D.
Bendixsen
Bendixsen is a surname most notably associated with Hans Ditlev Bendixsen, a prominent 19th-century Danish-American shipbuilder.
-
E.
Swanson
Swanson is the surname of Joe Swanson, a main supporting character and paraplegic police officer in the animated television series "Family Guy."
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243dfb4081909bc7a722843ffea7 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:59 p.m.