Triple
T6401630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lennox and Addington County |
E144076
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Hastings County |
E217843
|
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: Hastings County | Statement: [Lennox and Addington County, borders, Hastings County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hastings County Context triple: [Lennox and Addington County, borders, Hastings County]
-
A.
Hastings County
chosen
Hastings County is a large, predominantly rural county in eastern Ontario, Canada, known for its forests, lakes, and outdoor recreation opportunities.
-
B.
Burnet County
Burnet County is a central Texas county known for its scenic lakes, rolling hills, and outdoor recreation in the Texas Hill Country.
-
C.
Smith County
Smith County is a county in eastern Texas that includes the city of Tyler and serves as a regional hub for healthcare, education, and commerce.
-
D.
Smith County
Smith County is a rural county in central Mississippi known for its small communities, agriculture, and pine forests.
-
E.
Hunt County
Hunt County is a county in northeastern Texas that includes both rural communities and the city of Greenville as its county seat.
- 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_69c008dc56fc81908d43ffcc11d73bdd |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c068ade8c881908a0472f1de6b7c21 |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8ac74f44c8190953e486d3a315a64 |
completed | March 29, 2026, 4:37 a.m. |
Created at: March 22, 2026, 4:35 p.m.