Triple
T32248764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admission of Indonesia |
E823824
|
entity |
| Predicate | admittingOrganization |
P173880
|
FINISHED |
| Object | United Nations |
—
|
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: United Nations | Statement: [Admission of Indonesia, admittingOrganization, United Nations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: admittingOrganization Context triple: [Admission of Indonesia, admittingOrganization, United Nations]
-
A.
designatedAsFlagshipHospitalFor
Indicates that one hospital has been officially selected or recognized as the primary or leading flagship institution for another entity (such as a health system, region, or organization).
-
B.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
C.
admittedTo
Indicates that one entity has been formally accepted, enrolled, or granted entry into another entity, such as an institution, program, or facility.
-
D.
isPublicHospital
Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
-
E.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
- 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_69f3490cdda88190a9d61e11252a771f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bc351f388190baa983bc5776a296 |
completed | May 3, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:40 a.m.