Triple
T4550005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midway station (CTA) |
E110137
|
entity |
| Predicate | hasAirportWalkway |
P57943
|
FINISHED |
| Object | enclosed walkway |
—
|
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: enclosed walkway | Statement: [Midway station (CTA), hasAirportWalkway, enclosed walkway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirportWalkway Context triple: [Midway station (CTA), hasAirportWalkway, enclosed walkway]
-
A.
hasRunwayAccessVia
Indicates that an entity has access to a runway by means of a specified connecting route, facility, or intermediary.
-
B.
hasAirportTransitSystem
Indicates that an airport is equipped with a dedicated transit system for moving passengers or goods between its terminals, facilities, or areas.
-
C.
hasRunwayAccessTo
Indicates that one location or facility is directly connected to another via a usable runway, allowing aircraft to move between them without leaving runway infrastructure.
-
D.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
E.
hasEmergencyWalkway
Indicates that there is a designated emergency walkway available or present between the related entities.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f3f8348190868e274ac4df87ce |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:05 p.m.