Triple
T16701895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mumbai–Pune route |
E405872
|
entity |
| Predicate | travelTimeByExpressway |
P89543
|
FINISHED |
| Object | about 2.5 to 3 hours by car |
—
|
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: about 2.5 to 3 hours by car | Statement: [Mumbai–Pune route, travelTimeByExpressway, about 2.5 to 3 hours by car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeByExpressway Context triple: [Mumbai–Pune route, travelTimeByExpressway, about 2.5 to 3 hours by car]
-
A.
travelTimeTypical
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
B.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
C.
approximateDrivingTime
chosen
Indicates the estimated amount of time it takes to drive from one location to another under typical conditions.
-
D.
rangeHighwayApprox
Indicates that one entity is approximately within the range or vicinity of a highway associated with another entity.
-
E.
hasExpressLanes
Indicates that a roadway or transportation facility includes designated express lanes for faster or prioritized travel.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383326d7081909ef4c3b724876513 |
completed | April 18, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.