Triple
T8456995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Lille |
E199942
|
entity |
| Predicate | approximateTravelTime |
P46906
|
FINISHED |
| Object | about 1 hour 20 minutes |
—
|
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 1 hour 20 minutes | Statement: [London–Lille, approximateTravelTime, about 1 hour 20 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTravelTime Context triple: [London–Lille, approximateTravelTime, about 1 hour 20 minutes]
-
A.
hasApproximateWalkingTimeTo
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
-
B.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
C.
approximateTravelTimeToSheremetyevo
Indicates the estimated amount of time it typically takes to travel from a given location to Sheremetyevo.
-
D.
travelTimeTypical
chosen
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
E.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48f180c8190a71cf9d7248ade60 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.