Triple
T33142346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | نهر جيحون |
E848189
|
entity |
| Predicate | كان_حدًا_سياسيًا_بين |
P84932
|
FINISHED |
| Object | الدولة السامانية |
—
|
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: الدولة السامانية | Statement: [نهر جيحون, كان_حدًا_سياسيًا_بين, الدولة السامانية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: كان_حدًا_سياسيًا_بين Context triple: [نهر جيحون, كان_حدًا_سياسيًا_بين, الدولة السامانية]
-
A.
wasDividedBetween
Indicates that something was partitioned into portions that were allocated to two or more distinct recipients or groups.
-
B.
wasContestedBetween
Indicates that an event, position, or resource was the subject of competition or dispute involving two or more opposing parties.
-
C.
hasPoliticalComponent
Indicates that something includes, involves, or is influenced by political factors, interests, or considerations.
-
D.
wasFrontierBetween
chosen
Indicates that one entity historically served as the boundary or border region separating two other entities.
-
E.
isPoliticalBoundary
Indicates that one entity serves as a dividing line or border that separates distinct political or administrative jurisdictions.
- 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_69f3495961d88190b16ea542c2c5f825 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:28 a.m.