Triple
T17877901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid-Michigan |
E447004
|
entity |
| Predicate | containsCounty |
P5971
|
FINISHED |
| Object | Midland County |
—
|
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: Midland County | Statement: [Mid-Michigan, containsCounty, Midland County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Midland County Context triple: [Mid-Michigan, containsCounty, Midland County]
-
A.
Midland County
Midland County is a county in western Texas centered around the city of Midland, a major hub for the Permian Basin oil and gas industry.
-
B.
Midland County
chosen
Midland County is a county in central Michigan known for its role in the Great Lakes Bay Region and as the home of the city of Midland and major chemical industry operations.
-
C.
Blanco County
Blanco County is a rural county in central Texas known for its scenic Hill Country landscapes, small towns, and outdoor recreation along the Blanco River.
-
D.
Lawrence County
Lawrence County is a county in western South Dakota known for including part of the Black Hills region and the historic city of Deadwood.
-
E.
Lawrence County
Lawrence County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan region.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c0c46108190b8edef2572b5ba90 |
completed | April 19, 2026, 9:10 a.m. |
Created at: April 10, 2026, 10:18 a.m.