Triple
T34800793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Cardiff |
E1003212
|
entity |
| Predicate | hasApproximateFastRailJourneyTimeMinutes |
P194874
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [London–Cardiff, hasApproximateFastRailJourneyTimeMinutes, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateFastRailJourneyTimeMinutes Context triple: [London–Cardiff, hasApproximateFastRailJourneyTimeMinutes, 100]
-
A.
travelTimeFromTokyoByShinkansen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
-
B.
hasApproximateWalkingTimeTo
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
-
C.
railTravelTimeRangeHours
Indicates the range of time, in hours, that a journey by rail between the related entities is expected to take.
-
D.
commuterRailTravelTimeToManhattan
Indicates the travel time by commuter rail required to reach Manhattan from a given location.
-
E.
railwayTimeUsage
Indicates how much time is spent using or operating a railway within a given context or period.
- F. None of above. chosen
Provenance (4 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_69f76db543808190b188c6c86a91491b |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd8ccbd4c88190b13aae0673b3c821 |
completed | May 8, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69fd8ae2227c819089546f5c3629799e |
completed | May 8, 2026, 7:04 a.m. |
| PDg | Predicate description generation | batch_69fd8ccaee848190acd59d7d643ad062 |
completed | May 8, 2026, 7:12 a.m. |
Created at: May 3, 2026, 3:59 p.m.