Triple
T37953058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourg national public transport system |
E946792
|
entity |
| Predicate | serviceClassFreeOfCharge |
P31367
|
FINISHED |
| Object | second class |
—
|
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: second class | Statement: [Luxembourg national public transport system, serviceClassFreeOfCharge, second class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceClassFreeOfCharge Context triple: [Luxembourg national public transport system, serviceClassFreeOfCharge, second class]
-
A.
isFreeOfCharge
chosen
Indicates that no payment or fee is required for the associated action, service, or item.
-
B.
tollFreeForMostSections
Indicates that the majority of sections within something (such as a route, service, or facility) can be used without paying a toll.
-
C.
accessibleForFreeOrPaid
Indicates that the subject can be accessed either without cost or by paying a fee.
-
D.
isAccessibleForFreeParking
Indicates that a location or facility can be used for parking without any cost.
-
E.
featuresCharge
Indicates that one entity includes, offers, or is characterized by a particular charge (such as a fee, cost, or pricing component).
- 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_69f76ef64cf08190ad3e1114b62aac67 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 3, 2026, 4:20 p.m.