Triple
T17877910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid-Michigan |
E447004
|
entity |
| Predicate | hasRegionalCenterFor |
P117896
|
FINISHED |
| Object | education |
—
|
LITERAL 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: education | Statement: [Mid-Michigan, hasRegionalCenterFor, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalCenterFor Context triple: [Mid-Michigan, hasRegionalCenterFor, education]
-
A.
servesAsRegionalCenterFor
chosen
Indicates that one entity functions as the primary administrative, economic, or service hub for a surrounding region or group of entities.
-
B.
hasRegionalCentresIn
Indicates that an entity maintains one or more regional centers located in the specified place or area.
-
C.
hadRegionalCenter
Indicates that an entity possessed, operated, or was associated with a specific regional center serving a defined geographic area.
-
D.
administrativeCenterRegion
Indicates that a region serves as the administrative center or seat of government for another territorial unit.
-
E.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
- F. None of above.
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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c0c46108190b8edef2572b5ba90 |
completed | April 19, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.