Triple
T9705410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nashik Road railway station |
E234884
|
entity |
| Predicate | hasSuburbanConnectivity |
P68952
|
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: [Nashik Road railway station, hasSuburbanConnectivity, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuburbanConnectivity Context triple: [Nashik Road railway station, hasSuburbanConnectivity, yes]
-
A.
hasSuburbanService
chosen
Indicates that an entity provides or is connected to a public transportation service specifically serving suburban areas, typically linking suburbs with urban centers.
-
B.
hasSuburbanSection
Indicates that a larger route, line, or area includes a portion that passes through or serves a suburban region.
-
C.
hasSuburbanAreas
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
-
D.
isSuburbanCommunity
Indicates that a community is located in a suburban area, typically characterized by residential neighborhoods situated between urban centers and rural regions.
-
E.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
- 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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9da369b4819081f6ce01289ed725 |
completed | April 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69cd03b641408190942464eaf174c6b5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:19 p.m.