Triple
T1039933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy of Persian Language and Literature |
E22447
|
entity |
| Predicate | areaOfFocus |
P31
|
FINISHED |
| Object | modern Persian |
—
|
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: modern Persian | Statement: [Academy of Persian Language and Literature, areaOfFocus, modern Persian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaOfFocus Context triple: [Academy of Persian Language and Literature, areaOfFocus, modern Persian]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
engagementArea
Indicates the spatial region or scope within which an entity’s actions, influence, or interactions are intended to occur.
-
C.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
D.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
-
E.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.