Triple
T11095480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LOT Cargo |
E262365
|
entity |
| Predicate | usesBookingChannel |
P31089
|
FINISHED |
| Object | online cargo booking systems |
—
|
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: online cargo booking systems | Statement: [LOT Cargo, usesBookingChannel, online cargo booking systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBookingChannel Context triple: [LOT Cargo, usesBookingChannel, online cargo booking systems]
-
A.
hasBookingChannel
chosen
Indicates that an entity is associated with or obtained through a particular method or platform used to make a booking.
-
B.
usesBookingCode
Indicates that one entity makes use of a specific booking code associated with another entity or transaction.
-
C.
bookingModel
Indicates a relationship where an entity uses or is associated with a specific model or schema that defines how bookings are structured, processed, or represented.
-
D.
hasReservationFor
Indicates that an entity holds or is associated with a reservation for a specific event, service, or resource.
-
E.
allowsReservation
Indicates that one entity permits another entity to make or hold a reservation for its use or access.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0897188190b6c293b44990b3d4 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d7441aa3548190b92dbde57841c135 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.