Triple
T37313482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Circle–Wadala–Chembur corridor |
E926267
|
entity |
| Predicate | firstOperationalLineOf |
P99102
|
FINISHED |
| Object | Mumbai Monorail |
E55941
|
NE 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: Mumbai Monorail | Statement: [Jacob Circle–Wadala–Chembur corridor, firstOperationalLineOf, Mumbai Monorail]
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 (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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a409eed292c81908c6d5b4e7783f83a |
completed | June 28, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.