Triple
T636559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkmen language |
E16633
|
entity |
| Predicate | primaryScriptInTurkmenistan |
P6524
|
FINISHED |
| Object | Latin 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: Latin alphabet | Statement: [Turkmen language, primaryScriptInTurkmenistan, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryScriptInTurkmenistan Context triple: [Turkmen language, primaryScriptInTurkmenistan, Latin alphabet]
-
A.
primaryScript
chosen
Indicates the writing system or script that is chiefly used to represent the language or content of an entity.
-
B.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
C.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
D.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
E.
officialScriptOf
Indicates that one writing system is formally designated as the standard or legally recognized script used for a particular language, region, or 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee7fdbc8190858e42bb1bfdb3ff |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d0483908190a5ec42a7403c258e |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.