Triple
T21073070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi–Meerut Expressway |
E519156
|
entity |
| Predicate | hasDedicatedCycleTrack |
P1709
|
FINISHED |
| Object | in some stretches |
—
|
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: in some stretches | Statement: [Delhi–Meerut Expressway, hasDedicatedCycleTrack, in some stretches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDedicatedCycleTrack Context triple: [Delhi–Meerut Expressway, hasDedicatedCycleTrack, in some stretches]
-
A.
hasBicycleFacilities
chosen
Indicates that appropriate bicycle-related infrastructure or amenities are available at or associated with the subject.
-
B.
hasDedicatedLanes
Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
-
C.
hasWheelchairLanes
Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
-
D.
hasRideCycle
Indicates that one entity is associated with, or participates in, a recurring sequence or cycle of rides or ride operations.
-
E.
hasBicyclePolicy
Indicates that there exists a specific policy or set of rules governing the use, storage, or management of bicycles in relation to the subject.
- 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702d491a08190a9f5f28c0b72d38c |
completed | April 21, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:47 p.m.