Triple
T23407672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpensia Ski Jumping Centre |
E559979
|
entity |
| Predicate | hasPermanentSeats |
P152145
|
FINISHED |
| Object | about 8000 |
—
|
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: about 8000 | Statement: [Alpensia Ski Jumping Centre, hasPermanentSeats, about 8000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPermanentSeats Context triple: [Alpensia Ski Jumping Centre, hasPermanentSeats, about 8000]
-
A.
hasPermanentMembers
Indicates that certain members of a group or organization hold ongoing, non-temporary membership status.
-
B.
hasSeatsForConstituency
Indicates that a governing body or institution allocates or provides a certain number of representative seats for a specific constituency.
-
C.
permanentSeat
Indicates that an entity holds a seat or position that is intended to be ongoing and not subject to regular expiration, rotation, or reappointment.
-
D.
hasChairCount
Indicates the number of chairs associated with a given entity.
-
E.
governingBodySeats
Indicates the number of seats or positions an entity holds in a specified governing body.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50f3f90819084fb682597fee1e1 |
completed | April 29, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:38 p.m.