Triple
T424145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 80 |
E8167
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Toledo, Ohio |
E25661
|
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: Toledo, Ohio | Statement: [Interstate 80, passesThrough, Toledo, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toledo, Ohio Context triple: [Interstate 80, passesThrough, Toledo, Ohio]
-
A.
Toledo
Toledo is a historic Spanish city renowned for its medieval architecture, cultural heritage, and role as a major political and religious center in Spain’s history.
-
B.
Toledo
chosen
Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
-
C.
Columbus, Ohio
Columbus, Ohio is the capital and largest city of Ohio, known for its diverse economy, major universities, and role as a cultural and political center in the region.
-
D.
Norwalk, Ohio
Norwalk, Ohio is a small city in northern Ohio that serves as the county seat of Huron County and a regional hub for the surrounding rural communities.
-
E.
Akron
Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed3e4cc8190ba6aff3bd1adb06f |
completed | Feb. 28, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a44f522acc81909d16527bd08e458d |
completed | March 1, 2026, 2:38 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.