Triple
T8658393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ریاستجمهوری ایران |
E205481
|
entity |
| Predicate | مرتبط با |
P37
|
FINISHED |
| Object | رئیسجمهور ایران |
—
|
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: رئیسجمهور ایران | Statement: [ریاستجمهوری ایران, مرتبط با, رئیسجمهور ایران]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مرتبط با Context triple: [ریاستجمهوری ایران, مرتبط با, رئیسجمهور ایران]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
bondedWith
Indicates that two entities are joined by a strong, enduring connection or attachment, whether emotional, social, or structural.
-
C.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc486d576081908ad28749c7971432 |
completed | March 31, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:30 p.m.