Triple
T7126804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belmont station (CTA North Side) |
E166082
|
entity |
| Predicate | isUrbanStation |
P75010
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Belmont station (CTA North Side), isUrbanStation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanStation Context triple: [Belmont station (CTA North Side), isUrbanStation, yes]
-
A.
isSuburbanStationOf
Indicates that a station is located in a suburban area and functionally serves as a subsidiary or outlying station of a main or central station.
-
B.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
C.
isUrbanBridge
Indicates that a bridge is located within or closely associated with an urban (city or town) environment.
-
D.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
-
E.
isUrbanPark
Indicates that a location is designated and used as a public park within an urban or metropolitan area.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64ee8ac81909ee1c7cb1db3af33 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:44 p.m.