Triple
T37115482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cotton Green |
E919104
|
entity |
| Predicate | suburbanStyle |
P131786
|
FINISHED |
| Object | Mumbai Suburban Railway |
—
|
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: Mumbai Suburban Railway | Statement: [Cotton Green, suburbanStyle, Mumbai Suburban Railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanStyle Context triple: [Cotton Green, suburbanStyle, Mumbai Suburban Railway]
-
A.
hasSuburbanCharacter
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
B.
hasSuburbanForm
chosen
Indicates that one entity exhibits or possesses a suburban-style form, structure, or spatial pattern in relation to another.
-
C.
suburb
Indicates that one place is a residential district or outlying area that is part of or adjacent to a larger city or town.
-
D.
suburbanBelt
Indicates that one area forms a suburban belt or ring surrounding another, typically as a zone of residential or peripheral development around a core urban center.
-
E.
isSuburbanFocused
Indicates a focus, orientation, or specialization toward suburban areas, communities, or contexts.
- 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_69f76e9c57148190ba789dd059645bb9 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:15 p.m.