Triple
T16354416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Prime Minister of Afghanistan |
E397136
|
entity |
| Predicate | correspondsToTitleInPashto |
P89513
|
FINISHED |
| Object | معاون صدراعظم افغانستان |
—
|
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: معاون صدراعظم افغانستان | Statement: [Deputy Prime Minister of Afghanistan, correspondsToTitleInPashto, معاون صدراعظم افغانستان]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToTitleInPashto Context triple: [Deputy Prime Minister of Afghanistan, correspondsToTitleInPashto, معاون صدراعظم افغانستان]
-
A.
titleInPersian
Indicates that an entity’s title is expressed in the Persian language.
-
B.
titleInLanguage
chosen
Indicates that a specific title or name is expressed in a particular language.
-
C.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
D.
titleInLocalLanguage
Indicates that an entity’s title is expressed in the primary or native language of a specified place or community.
-
E.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facd80dc8190b08f0eecbf787240 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.