Triple
T27974704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | جلال آلاحمد |
E706454
|
entity |
| Predicate | رابطه ادبی |
P29936
|
FINISHED |
| Object | سیمین دانشور نویسندهٔ برجستهٔ ایرانی بود |
—
|
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: سیمین دانشور نویسندهٔ برجستهٔ ایرانی بود | Statement: [جلال آلاحمد, رابطه ادبی, سیمین دانشور نویسندهٔ برجستهٔ ایرانی بود]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: رابطه ادبی Context triple: [جلال آلاحمد, رابطه ادبی, سیمین دانشور نویسندهٔ برجستهٔ ایرانی بود]
-
A.
literaryRelationship
Indicates a relationship between entities that are connected through literature, such as authorship, influence, adaptation, or other text-based associations.
-
B.
literaryMuseOf
Indicates a relationship in which one entity serves as the creative inspiration or muse for another entity’s literary work.
-
C.
موضوع غزلیات
Indicates the subject or main thematic focus of the ghazals.
-
D.
hasLiteraryConnection
chosen
Indicates a relationship in which one entity is connected to another through a literary link, such as authorship, reference, influence, adaptation, or shared appearance in written works.
-
E.
القرابة
Indicates a kinship relationship or familial connection 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_69ef96b7f330819090f315318ba6977e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63b37b59c81909442178f8c0d0919 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 7:40 p.m.