Triple
T550287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramin |
E11822
|
entity |
| Predicate | commonInLanguage |
P907
|
FINISHED |
| Object | 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: Persian | Statement: [Ramin, commonInLanguage, Persian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonInLanguage Context triple: [Ramin, commonInLanguage, Persian]
-
A.
usedInLanguage
chosen
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
B.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
C.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
D.
otherLanguage
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
E.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49901e4e481909a5ed93c21ab37bd |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.