Triple
T12828529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travel.com.au |
E306721
|
entity |
| Predicate | hasBookingEngine |
P62319
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Travel.com.au, hasBookingEngine, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBookingEngine Context triple: [Travel.com.au, hasBookingEngine, true]
-
A.
hasBookingChannel
Indicates that an entity is associated with or obtained through a particular method or platform used to make a booking.
-
B.
hasBookingModel
Indicates that an entity is associated with or uses a particular booking model or reservation scheme.
-
C.
hasBookingOffice
Indicates that one entity maintains or is associated with a booking office where reservations or ticketing services are handled for it.
-
D.
hasReservationSystem
chosen
Indicates that an entity uses or is equipped with a system for managing reservations or bookings.
-
E.
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.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:34 p.m.