Triple
T9021645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMI |
E215737
|
entity |
| Predicate | distanceFromChampaign |
P85750
|
FINISHED |
| Object | approximately 6 miles south |
—
|
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: approximately 6 miles south | Statement: [CMI, distanceFromChampaign, approximately 6 miles south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromChampaign Context triple: [CMI, distanceFromChampaign, approximately 6 miles south]
-
A.
distanceFromChicagoLoop
Indicates the spatial distance between an entity’s location and the Chicago Loop area.
-
B.
distanceToBloomington
Indicates the spatial distance between a given entity’s location and the location of Bloomington.
-
C.
distanceFromChicagoUnionStation
Indicates the measured distance between a given location and Chicago Union Station.
-
D.
distanceToChicagoLoop
Indicates the spatial distance between a given location and Chicago’s central business district (the Loop).
-
E.
distanceFromDesMoines
Indicates the physical distance between a given location and the city of Des Moines.
- F. None of above. chosen
Provenance (4 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_69ca83a38aa88190bf1bb80c4548b5e2 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a43add08190983b7ac88576fd7e |
completed | April 1, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f6dec4081909379bd57c02a5710 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:07 p.m.