Triple
T526055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Olympic Committee |
E10920
|
entity |
| Predicate | membershipCount |
P9078
|
FINISHED |
| Object | 100+ individual members |
—
|
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: 100+ individual members | Statement: [International Olympic Committee, membershipCount, 100+ individual members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: membershipCount Context triple: [International Olympic Committee, membershipCount, 100+ individual members]
-
A.
numberOfAssociateMembers
Indicates the total count of associate members linked to a given entity.
-
B.
registerCount
Indicates the number of registers associated with or allocated to a given entity in a system.
-
C.
hasCurrentNumberOfMembers
chosen
Indicates the current count of members associated with a given entity.
-
D.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
E.
hasMembers
Indicates that a group, organization, or collection includes certain entities as its members.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d0d22081908aad915482d39e74 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0198ecc8190883849e5a8245963 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.