Triple
T25283594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiang Mai Initiative Multilateralisation |
E633878
|
entity |
| Predicate | hasTotalSize |
P162577
|
FINISHED |
| Object | 240 billion U.S. dollars |
—
|
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: 240 billion U.S. dollars | Statement: [Chiang Mai Initiative Multilateralisation, hasTotalSize, 240 billion U.S. dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTotalSize Context triple: [Chiang Mai Initiative Multilateralisation, hasTotalSize, 240 billion U.S. dollars]
-
A.
hasTotalNumber
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
-
B.
hasSize
Indicates that one entity possesses a particular physical magnitude or extent, such as length, volume, or overall dimensions.
-
C.
hasSizeDescriptor
Indicates that an entity is associated with a qualitative description of its size (e.g., small, large, huge).
-
D.
commonTotalLength
Indicates that the entities share the same overall measured length.
-
E.
hasNetworkSize
Indicates the total number of nodes, members, or connections that make up a given network.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f627ad6d4c81909796d39d78e414f9 |
completed | May 2, 2026, 4:34 p.m. |
Created at: April 21, 2026, 1:19 p.m.