Triple
T30535604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lombard Metra station |
E777133
|
entity |
| Predicate | distanceFromChicagoOgilvie |
P89024
|
FINISHED |
| Object | approximately 19 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 19 miles | Statement: [Lombard Metra station, distanceFromChicagoOgilvie, approximately 19 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromChicagoOgilvie Context triple: [Lombard Metra station, distanceFromChicagoOgilvie, approximately 19 miles]
-
A.
distanceFromOgilvieTransportationCenter
chosen
Indicates the measured distance between a given location and the Ogilvie Transportation Center.
-
B.
distanceFromChicagoUnionStation
Indicates the measured distance between a given location and Chicago Union Station.
-
C.
distanceFromChicagoTerminus
Indicates the measured distance of an entity from the Chicago terminus point along a specified route or network.
-
D.
distanceToChicagoLoop
Indicates the spatial distance between a given location and Chicago’s central business district (the Loop).
-
E.
distanceToElgin
Indicates the spatial distance between a given entity and the location identified as Elgin.
- 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_69f2249d183c8190b79937c1768d2163 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a012efebda88190a90c8f650e4b1ee9 |
completed | May 11, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_6a01298cc604819087c836659c128926 |
completed | May 11, 2026, 12:57 a.m. |
Created at: April 29, 2026, 8:18 p.m.