Triple
T22455199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | York—Simcoe |
E555096
|
entity |
| Predicate | containsCommunity |
P8617
|
FINISHED |
| Object | Sharon |
—
|
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: Sharon | Statement: [York—Simcoe, containsCommunity, Sharon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sharon Context triple: [York—Simcoe, containsCommunity, Sharon]
-
A.
Sharon
Sharon is a suburban town in Norfolk County, Massachusetts, known for its residential character, natural conservation areas, and proximity to Boston.
-
B.
Sharon
chosen
Sharon is a small community within the town of East Gwillimbury in Ontario, Canada, known for its residential character and local heritage.
-
C.
Sharon
Sharon is a fictional character from Frederick Buechner’s comic novel sequence *The Book of Bebb*, which follows the eccentric evangelist Leo Bebb and those in his orbit.
-
D.
Sharon
Sharon is the given first name of American actress S. Epatha Merkerson, best known for her long-running role as Lieutenant Anita Van Buren on the television series "Law & Order."
-
E.
Sharon
Sharon is the central protagonist of the Christian apocalyptic novel "The Rapture," around whom the story’s end-times events and spiritual struggles revolve.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4e2bd4819083e5bed44e9776c6 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 16, 2026, 8:48 p.m.