Triple
T20564707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Association of African and Malagasy States |
E504936
|
entity |
| Predicate | memberCountries |
P86354
|
FINISHED |
| Object | African states |
—
|
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: African states | Statement: [Association of African and Malagasy States, memberCountries, African states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberCountries Context triple: [Association of African and Malagasy States, memberCountries, African states]
-
A.
memberNation
chosen
Indicates that one entity is a nation that belongs to, or holds membership in, an international organization or group represented by the other entity.
-
B.
countryMembers
Indicates that certain entities are members or constituent parts of a specified country.
-
C.
countryJoined
Indicates that a country became a member of, or formally entered into, a specific organization, union, alliance, or agreement.
-
D.
hasNonRegionalMemberCountries
Indicates that an organization includes member countries that are not part of the primary geographic region with which the organization is associated.
-
E.
relatedCountry
Indicates that there is a relevant or associated relationship between an entity and a specified country, without specifying the exact nature of that relationship.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a15c988190ba93823df119ca4d |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.