Triple
T5501303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ШОС |
E144333
|
entity |
| Predicate | характер |
P662
|
FINISHED |
| Object | постоянно действующая организация |
—
|
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: постоянно действующая организация | Statement: [ШОС, характер, постоянно действующая организация]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: характер Context triple: [ШОС, характер, постоянно действующая организация]
-
A.
associatedCharacterTrait
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
B.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
C.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
D.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
- 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_69c008f5a2748190bce7a39aabf87a6d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f08c2a4819093e772a1497c7ecc |
completed | March 22, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69c01b052f3c81909f71c6add0f35a6f |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:32 p.m.