Triple
T8241694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ola Outstation |
E192550
|
entity |
| Predicate | offersVehicleCategory |
P1776
|
FINISHED |
| Object | sedan |
—
|
LITERAL 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: sedan | Statement: [Ola Outstation, offersVehicleCategory, sedan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersVehicleCategory Context triple: [Ola Outstation, offersVehicleCategory, sedan]
-
A.
vehicleType
chosen
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
vehicleTypeFocus
Indicates that the relationship or action specifically concerns or emphasizes a particular type or category of vehicle.
-
C.
vehicleRegistrationCategory
Indicates the classification or type of registration assigned to a vehicle under a specific regulatory or administrative scheme.
-
D.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
E.
offersProductCategory
Indicates that a provider or seller makes products belonging to a specific product category available.
- F. None of above.
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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb783f67708190a4e1c4078c3a6fb0 |
completed | March 31, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.