Triple
T18333941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vernon Wells |
E439218
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Vernon |
—
|
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: Vernon | Statement: [Vernon Wells, givenName, Vernon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vernon Context triple: [Vernon Wells, givenName, Vernon]
-
A.
Vernon
Vernon is a fictional character portrayed by actor Lucas Black, likely in a film or television production.
-
B.
Vernon
Vernon is a small, heavily industrial city located just south of downtown Los Angeles in Southern California.
-
C.
Vernon
Vernon is a suburban town in north-central Connecticut that forms part of the Greater Hartford metropolitan area.
-
D.
Vernon
chosen
Vernon is a masculine given name of English origin, historically used in various English-speaking countries.
-
E.
Vernon
Vernon is a small city in British Columbia, Canada, known for its lakes, outdoor recreation, and role as a service and tourism hub in the Okanagan region.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecbc76c8190a80c0c8c8bce1cbd |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.