Triple
T31012339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid–Barcelona high-speed line |
E790239
|
entity |
| Predicate | travelTimeReductionComparedToClassicLine |
P71530
|
FINISHED |
| Object | significant |
—
|
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: significant | Statement: [Madrid–Barcelona high-speed line, travelTimeReductionComparedToClassicLine, significant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeReductionComparedToClassicLine Context triple: [Madrid–Barcelona high-speed line, travelTimeReductionComparedToClassicLine, significant]
-
A.
timeSavedComparedToOlderRoutes
chosen
Indicates the amount of time saved by using the current route compared to older or previously used routes.
-
B.
relativeSpeedComparedToConventionalTrains
Indicates how the speed of something compares to that of conventional trains, typically expressing whether it is faster, slower, or similar.
-
C.
reducedTravelTimeFrom
Indicates that one entity has caused or experienced a decrease in the amount of time required to travel from a specified origin entity.
-
D.
travelTimeOnShanghaiRoute
Indicates the duration required to travel along a specified route in Shanghai.
-
E.
transportModeComparedWith
Indicates a comparison between two entities regarding the mode of transport they use or are associated with.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 29, 2026, 8:57 p.m.