Triple
T7335817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downers Grove Main Street station |
E169123
|
entity |
| Predicate | hasUnderpassOrOverpass |
P24311
|
FINISHED |
| Object | pedestrian underpass |
—
|
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: pedestrian underpass | Statement: [Downers Grove Main Street station, hasUnderpassOrOverpass, pedestrian underpass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderpassOrOverpass Context triple: [Downers Grove Main Street station, hasUnderpassOrOverpass, pedestrian underpass]
-
A.
hasUnderpass
chosen
Indicates that one location or structure includes or is connected by an underpass beneath another feature or pathway.
-
B.
hasPedestrianOverpass
Indicates that there exists a pedestrian overpass connecting or spanning parts of the referenced location or infrastructure.
-
C.
hasUndergroundSection
Indicates that an entity includes a portion or segment that is located below ground level.
-
D.
hasUndergroundConnections
Indicates that one entity is linked to another through subterranean or hidden passageways, networks, or channels.
-
E.
hasViaduct
Indicates that one entity possesses, includes, or is connected by a viaduct in relation to another 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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.