Triple
T23776896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supreme Leader of the Islamic Emirate of Afghanistan |
E587699
|
entity |
| Predicate | native_name_language |
P28203
|
FINISHED |
| Object | Pashto |
—
|
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: Pashto | Statement: [Supreme Leader of the Islamic Emirate of Afghanistan, native_name_language, Pashto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: native_name_language Context triple: [Supreme Leader of the Islamic Emirate of Afghanistan, native_name_language, Pashto]
-
A.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
B.
nativeLanguageFamilyName
Indicates the name of the language family to which an entity’s native language belongs.
-
C.
originalNameLanguage
chosen
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
D.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
E.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native 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_69e2490d245881909028226a1393d624 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c46d55588190ad9c7e3c729b6b17 |
completed | April 29, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:16 p.m.