Triple
T9186632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kermanic languages |
E220474
|
entity |
| Predicate | areDifferentiatedFrom |
P6335
|
FINISHED |
| Object | Southwestern Iranian languages |
—
|
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: Southwestern Iranian languages | Statement: [Kermanic languages, areDifferentiatedFrom, Southwestern Iranian languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areDifferentiatedFrom Context triple: [Kermanic languages, areDifferentiatedFrom, Southwestern Iranian languages]
-
A.
differentiatedFrom
chosen
Indicates that one entity is distinguished or set apart from another by identifying differences between them.
-
B.
differIn
Indicates that two entities are not the same in at least one specified aspect, attribute, or value.
-
C.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
D.
mechanicallyDistinctFrom
Indicates that two entities differ in their mechanical properties, structure, or behavior such that they are not mechanically equivalent or interchangeable.
-
E.
categoryDistinguishedFrom
Indicates that one category is explicitly distinguished from another, clarifying that they are separate and should not be confused.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31a52508190a83ccd76f3aa039b |
completed | April 1, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.