Triple
T4066928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Tajikistan |
E86345
|
entity |
| Predicate | nativeLanguageOfTitle |
P29322
|
FINISHED |
| Object | Tajik |
—
|
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: Tajik | Statement: [President of Tajikistan, nativeLanguageOfTitle, Tajik]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeLanguageOfTitle Context triple: [President of Tajikistan, nativeLanguageOfTitle, Tajik]
-
A.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
B.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
-
C.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
D.
languageOfAlternativeTitle
Indicates the language in which an alternative or variant title of an entity is expressed.
-
E.
nameInOriginalLanguage
chosen
Indicates that an entity’s name is given in its original or native language form.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf73a1c81909f1741f4ecf55f98 |
completed | March 9, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.