Triple
T8192964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ola Share |
E191358
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Ola Cabs |
E36498
|
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 Cabs | Statement: [Ola Share, operator, Ola Cabs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ola Cabs Context triple: [Ola Share, operator, Ola Cabs]
-
A.
Ola Cabs
chosen
Ola Cabs is a major Indian ride-hailing company offering app-based transportation and mobility services across numerous cities in India and other countries.
-
B.
Careem
Careem is a Dubai-based ride-hailing and delivery company operating across the Middle East, North Africa, and South Asia, acquired by Uber to expand its presence in the region.
-
C.
Meru Cabs
Meru Cabs is an Indian radio taxi and ride-hailing company that was one of the country’s early organized cab service providers.
-
D.
Uber Pro
Uber Pro is a rewards and loyalty program that provides benefits and incentives to Uber drivers based on their performance and activity.
-
E.
GrabTaxi
GrabTaxi is a Southeast Asian ride-hailing and transportation platform that began as MyTeksi in Malaysia before expanding regionally under the Grab brand.
- 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_69ce4d731b248190a440e1289e655b74 |
completed | April 2, 2026, 11:05 a.m. |
Created at: March 30, 2026, 5:42 p.m.