Triple
T6179781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMS Collaboration |
E137911
|
entity |
| Predicate | hasMembersFromCountries |
P19946
|
FINISHED |
| Object | over 50 countries |
—
|
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: over 50 countries | Statement: [CMS Collaboration, hasMembersFromCountries, over 50 countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMembersFromCountries Context triple: [CMS Collaboration, hasMembersFromCountries, over 50 countries]
-
A.
hasNonRegionalMemberCountries
Indicates that an organization includes member countries that are not part of the primary geographic region with which the organization is associated.
-
B.
hasMemberJurisdictions
Indicates that an administrative or organizational entity includes specific jurisdictions as its constituent members.
-
C.
memberOfThroughCountry
Indicates that an entity is a member of another entity (such as an organization or group) by virtue of, or via, its association with a specific country.
-
D.
countryMembers
Indicates that certain entities are members or constituent parts of a specified country.
-
E.
countryOfOriginOfMembers
chosen
Indicates that one entity is the country from which the members of another entity originate.
- 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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05dcb77948190b5385438f81bf0a8 |
completed | March 22, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69c055fa0a808190bda37832e3ac150c |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.