Triple
T4377091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gothia Cup |
E99032
|
entity |
| Predicate | accommodationModel |
P56467
|
FINISHED |
| Object | school accommodation |
—
|
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: school accommodation | Statement: [Gothia Cup, accommodationModel, school accommodation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accommodationModel Context triple: [Gothia Cup, accommodationModel, school accommodation]
-
A.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
B.
rentalModel
Indicates that one entity is used or provided to another under a specific rental arrangement, defining how the rental relationship is structured or operates.
-
C.
reservationSystem
Indicates a system or process that manages the creation, modification, and tracking of reservations or bookings between parties.
-
D.
reservationLocatedIn
Indicates that a reservation (such as a booking or held resource) is situated within or associated with a specific location or place.
-
E.
hotelConnection
Indicates a relationship where one entity is linked or associated with a hotel, such as being located in, connected to, or serviced by that hotel.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3523ed220819090cef1a7933489d9 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:18 p.m.