Triple
T8192895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ola Micro |
E191356
|
entity |
| Predicate | bookingMethod |
P1030
|
FINISHED |
| Object | Ola mobile app |
E197052
|
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: Ola mobile app | Statement: [Ola Micro, bookingMethod, Ola mobile app]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ola mobile app Context triple: [Ola Micro, bookingMethod, Ola mobile app]
-
A.
Ola Share
Ola Share is a ride-sharing service by Ola that allows multiple passengers heading in the same direction to share a cab and split the fare.
-
B.
Ola
chosen
Ola is a major Indian ride-hailing and mobility platform offering cab, auto-rickshaw, and other transportation services via its mobile app.
-
C.
Ola
Ola is a small urban locality in Russia’s Magadan Oblast, situated in the Russian Far East along the Sea of Okhotsk.
-
D.
Ola Outstation
Ola Outstation is a long-distance ride service from Ola Cabs that lets users book intercity and out-of-town trips via the Ola app.
-
E.
Ola Micro
Ola Micro is a budget-friendly ride option from Indian ride-hailing company Ola, offering low-cost cab services for short-distance urban travel.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82c5b6948190a583c096fb0a6c71 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5c1d7aa48190adbbce88b3bed1a3 |
completed | March 31, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cceda1b22c8190acc1a2cd0fe36b70 |
completed | April 1, 2026, 10:04 a.m. |
Created at: March 30, 2026, 5:42 p.m.