Triple
T9461471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سيحون |
E228154
|
entity |
| Predicate | يرتبط_بأزمة |
P25894
|
FINISHED |
| Object | انحسار مياه بحر آرال |
—
|
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: انحسار مياه بحر آرال | Statement: [سيحون, يرتبط_بأزمة, انحسار مياه بحر آرال]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يرتبط_بأزمة Context triple: [سيحون, يرتبط_بأزمة, انحسار مياه بحر آرال]
-
A.
crisisRelatedTo
chosen
Indicates a relationship where one situation, event, or condition is connected to, associated with, or relevant to a crisis.
-
B.
associatedBreak
Indicates a relationship where one entity is linked to a specific break, interruption, or pause that is relevant to its state, schedule, or operation.
-
C.
associatedFault
Indicates a relationship where a given entity is linked to, or occurs in connection with, a specific fault or error condition.
-
D.
breakupLinkedTo
Indicates a causal or associative relationship where a breakup is connected to, influenced by, or results from another event, factor, or entity.
-
E.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fcc8b1881908aa6ee13ab195330 |
completed | April 1, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69cca55caaa8819089c5138e014892d3 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:52 p.m.