Triple
T885337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl Monroe |
E19117
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Vernon |
E101458
|
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: Vernon | Statement: [Earl Monroe, givenName, Vernon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vernon Context triple: [Earl Monroe, givenName, Vernon]
-
A.
Vernon
chosen
Vernon is a town in northern France on the Seine River, known for its picturesque setting that attracted artists such as Pierre Bonnard.
-
B.
Weston
Weston is a suburban town in eastern Massachusetts known for its residential character, conservation land, and commuter access to Boston.
-
C.
Twain Harte
Twain Harte is a small mountain resort town in California’s Sierra Nevada known for its pine forests, outdoor recreation, and proximity to Yosemite National Park.
-
D.
Springwood
Springwood is the historic Hudson River estate in Hyde Park, New York, best known as the lifelong home and presidential library site of Franklin D. Roosevelt.
-
E.
Springwood
Springwood is a major town in the Lower Blue Mountains region of New South Wales, Australia, known as a residential and commercial hub amid bushland and scenic surroundings.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ace5e15c81908cc2e648c9cd52f2 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3b9b7eb88190b7fa4f9dbcc73d64 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:39 p.m.