Triple
T12019524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brussels North–South railway axis |
E286110
|
entity |
| Predicate | dailyTrainTraffic |
P13069
|
FINISHED |
| Object | over 1,000 trains per day |
—
|
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: over 1,000 trains per day | Statement: [Brussels North–South railway axis, dailyTrainTraffic, over 1,000 trains per day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dailyTrainTraffic Context triple: [Brussels North–South railway axis, dailyTrainTraffic, over 1,000 trains per day]
-
A.
railwayTraffic
Indicates the presence, flow, or management of train movements along railway lines between locations.
-
B.
peakDailyTrains
chosen
Indicates the maximum number of trains operating per day on a given route, line, or segment during its busiest period.
-
C.
railwayTrafficDirection
Indicates the customary side of the track on which trains are operated or expected to run within a given railway system or segment.
-
D.
railwayLineUsage
Indicates how a railway line is used, such as the type or purpose of traffic or operations it supports.
-
E.
followingTrainStatus
Indicates that one entity is tracking or monitoring the current operational status or progress of a train.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902b6ebbc8190b13c44a61c6f81b9 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.