Triple
T9055158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilaks |
E216977
|
entity |
| Predicate | usesScriptForLanguage |
P56657
|
FINISHED |
| Object | Persian alphabet |
—
|
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 alphabet | Statement: [Gilaks, usesScriptForLanguage, Persian alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesScriptForLanguage Context triple: [Gilaks, usesScriptForLanguage, Persian alphabet]
-
A.
scriptUsedForLanguage
chosen
Indicates that a particular writing script is employed to write or represent a given language.
-
B.
usesScriptDerivedFrom
Indicates that one entity employs a writing system that is historically or structurally derived from the script used by another entity.
-
C.
usesLanguageRuntime
Indicates that an entity operates using, depends on, or is executed within a specific language runtime environment.
-
D.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
E.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a7488188190b3dd6bc2f2377503 |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee6d83c819095d8ed0779aa8511 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.