Triple
T135537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish language |
E2737
|
entity |
| Predicate | majorPeriodOfLanguagePurification |
P5215
|
FINISHED |
| Object | 20th century |
—
|
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: 20th century | Statement: [Turkish language, majorPeriodOfLanguagePurification, 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorPeriodOfLanguagePurification Context triple: [Turkish language, majorPeriodOfLanguagePurification, 20th century]
-
A.
languageOfEarliestForm
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
-
B.
hasLanguageRevitalizationEfforts
Indicates that there are organized actions or initiatives aimed at preserving, strengthening, or reviving the use of a particular language.
-
C.
hasNationalLanguageRegulator
Indicates that an entity has an official body or authority responsible for regulating and overseeing its national language.
-
D.
historicallySpokenIn
Indicates that a language was used for spoken communication in a particular place or region during a past historical period.
-
E.
hasOfficialOrthography
Indicates that an entity has a formally recognized and standardized system for writing its language or name.
- F. None of above. chosen
Provenance (4 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a3ad908190b6a8652f09ae0cbb |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.