Triple
T24423575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Shore region of Chicago metropolitan area |
E615791
|
entity |
| Predicate | distanceToDowntownChicago |
P24863
|
FINISHED |
| Object | approximately 10–30 miles |
—
|
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 10–30 miles | Statement: [North Shore region of Chicago metropolitan area, distanceToDowntownChicago, approximately 10–30 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDowntownChicago Context triple: [North Shore region of Chicago metropolitan area, distanceToDowntownChicago, approximately 10–30 miles]
-
A.
distanceFromChicagoLoop
Indicates the spatial distance between an entity’s location and the Chicago Loop area.
-
B.
distanceToChicagoLoop
chosen
Indicates the spatial distance between a given location and Chicago’s central business district (the Loop).
-
C.
distanceFromChicagoUnionStation
Indicates the measured distance between a given location and Chicago Union Station.
-
D.
distanceFromUrbana
Indicates the measured spatial distance between a given entity or location and Urbana.
-
E.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
- 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296a4e3e4819094ac0941da5ca641 |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:14 a.m.