Triple
T37313482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Circle–Wadala–Chembur corridor |
E926267
|
entity |
| Predicate | firstOperationalLineOf |
—
|
GENERATED |
| Object | Mumbai Monorail |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstOperationalLineOf Context triple: [Jacob Circle–Wadala–Chembur corridor, firstOperationalLineOf, Mumbai Monorail]
-
A.
firstCommercialLine
Indicates that the subject is the first commercial line (e.g., initial business or product line) associated with the object.
-
B.
firstOperationalUse
Indicates the point in time or context when something is used operationally for the very first time.
-
C.
firstLineInOperation
chosen
Indicates that one entity is the first line or initial step executed within a particular operation or process.
-
D.
firstOperationalRole
Indicates the initial functional position, duty, or role an entity first performs or holds in an operational context.
-
E.
firstModelLineOf
Indicates that one entity is the first line of a model or modeling construct associated with another entity.
- F. None of above.
Provenance (1 batch)
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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:16 p.m.