Triple
T36637855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ETIAS |
E904508
|
entity |
| Predicate | appliesToTravelType |
P200533
|
FINISHED |
| Object | short stays up to 90 days in any 180-day period |
—
|
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: short stays up to 90 days in any 180-day period | Statement: [ETIAS, appliesToTravelType, short stays up to 90 days in any 180-day period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToTravelType Context triple: [ETIAS, appliesToTravelType, short stays up to 90 days in any 180-day period]
-
A.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
-
B.
appliesToTransportMode
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
-
C.
appliesToPassengerType
Indicates that a rule, condition, or attribute is relevant or restricted to a specific type or category of passenger.
-
D.
fareAppliesTo
Indicates that a specific fare is applicable to a particular trip, service, passenger category, or travel condition.
-
E.
offersClassOfTravel
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
- 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_69f76e6c63e48190b1d0c3a79a6c7406 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff9361943c81909544203cbc998a69 |
completed | May 9, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69ff913138a08190b59bdc9d8d199eb3 |
completed | May 9, 2026, 7:55 p.m. |
| PDg | Predicate description generation | batch_69ff935f48808190aa6f4834f59d45b8 |
completed | May 9, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:11 p.m.