Triple
T4839177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magadan Time |
E108135
|
entity |
| Predicate | appliesToCity |
P4810
|
FINISHED |
| Object |
Ola
Ola is a small urban locality in Russia’s Magadan Oblast, situated in the Russian Far East along the Sea of Okhotsk.
|
E474828
|
NE FINISHED |
How this triple was built (4 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 | Statement: [Magadan Time, appliesToCity, Ola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ola Context triple: [Magadan Time, appliesToCity, Ola]
-
A.
Ola
Ola is a major Indian ride-hailing and mobility platform offering cab, auto-rickshaw, and other transportation services via its mobile app.
-
B.
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.
-
C.
Ola Auto
Ola Auto is a ride-hailing service segment of Ola Cabs that connects passengers with auto-rickshaw drivers via the Ola mobile app.
-
D.
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.
-
E.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ola Triple: [Magadan Time, appliesToCity, Ola]
Generated description
Ola is a small urban locality in Russia’s Magadan Oblast, situated in the Russian Far East along the Sea of Okhotsk.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ola Target entity description: Ola is a small urban locality in Russia’s Magadan Oblast, situated in the Russian Far East along the Sea of Okhotsk.
-
A.
Ola
Ola is a major Indian ride-hailing and mobility platform offering cab, auto-rickshaw, and other transportation services via its mobile app.
-
B.
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.
-
C.
Ola Auto
Ola Auto is a ride-hailing service segment of Ola Cabs that connects passengers with auto-rickshaw drivers via the Ola mobile app.
-
D.
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.
-
E.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
- F. None of above. chosen
Provenance (5 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ce4a5108190aede620d5dde1f81 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cc5861881908ad3838168325a34 |
completed | March 21, 2026, 8:54 a.m. |
| NEDg | Description generation | batch_69be5ed104e48190b01ea97094be6a96 |
completed | March 21, 2026, 9:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be5fe07d708190ba0dde4c081e15c6 |
completed | March 21, 2026, 9:07 a.m. |
Created at: March 20, 2026, 1:25 p.m.