Triple
T23703337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court of Arbitration for Sport |
E585651
|
entity |
| Predicate | hasSeatAtEvents |
P150851
|
FINISHED |
| Object | Olympic Games |
—
|
NE NERFINISHED |
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: Olympic Games | Statement: [Court of Arbitration for Sport, hasSeatAtEvents, Olympic Games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatAtEvents Context triple: [Court of Arbitration for Sport, hasSeatAtEvents, Olympic Games]
-
A.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
B.
hasVenueFor
Indicates that one entity provides or serves as the location or setting where an event, activity, or function takes place for another entity.
-
C.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
D.
hasAttended
chosen
Indicates that an entity has been present at or participated in a particular event, place, or gathering.
-
E.
hasHostedVenue
Indicates that a particular venue has served as the location for hosting a specific event or activity.
- 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_69e24904bd508190abfcb74855de2918 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b684e0a88190b7edeb102585ae9d |
completed | April 29, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:53 p.m.