Triple
T26940132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Güzelyurt District |
E678489
|
entity |
| Predicate | hasDeFactoOfficialLanguage |
P112296
|
FINISHED |
| Object | Turkish |
—
|
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: Turkish | Statement: [Güzelyurt District, hasDeFactoOfficialLanguage, Turkish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeFactoOfficialLanguage Context triple: [Güzelyurt District, hasDeFactoOfficialLanguage, Turkish]
-
A.
hasOfficialCountryLanguage
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
B.
hasLanguageOfficial
chosen
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
C.
declaresOfficialLanguageOf
Indicates that an authority formally designates a particular language as the official language of a specified entity or jurisdiction.
-
D.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
E.
hasOfficialLanguageOnOneSide
Indicates that one side or party in a relationship has a designated official language associated specifically with 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 27, 2026, 6:18 a.m.