Triple
T34550783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quincy Street (Chicago) |
E887054
|
entity |
| Predicate | hasAssociatedTransitStation |
P69365
|
FINISHED |
| Object | Quincy station (CTA) |
—
|
NE NERFINISHED |
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: Quincy station (CTA) | Statement: [Quincy Street (Chicago), hasAssociatedTransitStation, Quincy station (CTA)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedTransitStation Context triple: [Quincy Street (Chicago), hasAssociatedTransitStation, Quincy station (CTA)]
-
A.
hasTransitAccessTo
chosen
Indicates that one place or entity is reachable from another via public or shared transportation services.
-
B.
appliesToTransitStation
Indicates that something (such as a rule, feature, condition, or attribute) is specifically relevant or applicable to a transit station.
-
C.
associatedWithTransitLine
Indicates that an entity has a connection or linkage to a specific transit line, such as being part of, served by, or otherwise related to that line.
-
D.
associatedWithTransitSystem
Indicates that an entity has a connection or involvement with a particular transit or transportation system.
-
E.
hasInterchangeStationWith
Indicates that two transportation lines, routes, or systems share a station where passengers can transfer between them.
- 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 1, 2026, 2:02 a.m.