Triple
T3682834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aurora, Illinois |
E78149
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Kane County |
E17057
|
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: Kane County | Statement: [Aurora, Illinois, county, Kane County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kane County Context triple: [Aurora, Illinois, county, Kane County]
-
A.
Will County
Will County is a county in northeastern Illinois that includes the city of Joliet and forms part of the Chicago metropolitan area.
-
B.
Kane County, Illinois
chosen
Kane County, Illinois is a suburban county west of Chicago that forms part of the greater Chicago metropolitan area.
-
C.
Warren County
Warren County is a largely rural county in northwestern New Jersey known for its small towns, farmland, and role as a residential area for commuters in the New York metropolitan region.
-
D.
Warren County
Warren County is a county in northeastern New York State known for encompassing much of the Adirondack Mountains and popular tourist destinations such as Lake George.
-
E.
Whiteside County
Whiteside County is a county in northwestern Illinois known for its mix of small rural communities and agricultural landscapes.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4948cc48190ab1f59cc4a2437cc |
completed | March 8, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f021fe148190af7ba4b36caa0ce2 |
completed | March 14, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:25 p.m.