Triple
T34411297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Economy Skycouch |
E883273
|
entity |
| Predicate | bookingUnit |
P76710
|
FINISHED |
| Object | sold per row rather than per individual seat |
—
|
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: sold per row rather than per individual seat | Statement: [Economy Skycouch, bookingUnit, sold per row rather than per individual seat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookingUnit Context triple: [Economy Skycouch, bookingUnit, sold per row rather than per individual seat]
-
A.
bookingControl
Indicates that one entity has the authority or mechanism to manage, modify, or regulate the booking or reservation of another entity.
-
B.
bookingModel
chosen
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.
-
C.
reservationSystem
Indicates a system or process that manages the creation, modification, and tracking of reservations or bookings between parties.
-
D.
reservationAlsoKnownAs
Indicates that a reservation is referred to by an alternative name or alias.
-
E.
bookingPattern
Indicates a recurring or characteristic way in which bookings are made, such as their timing, frequency, or sequence.
- 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_69f349c1f2208190a09a489bb8b2719d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:59 a.m.