Triple
T2613930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghan |
E58840
|
entity |
| Predicate | nationalLanguage |
P236
|
FINISHED |
| Object | Dari |
E109613
|
NE 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: Dari | Statement: [Afghan, nationalLanguage, Dari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dari Context triple: [Afghan, nationalLanguage, Dari]
-
A.
Dari
chosen
Dari is a variety of the Persian language primarily spoken in Afghanistan and used in media, education, and government there.
-
B.
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
-
C.
Daule
Daule is a town and canton in coastal Ecuador known for its rice production and location within the Guayas Province.
-
D.
Adad
Adad is the Mesopotamian storm and rain god, associated with thunder, fertility, and divine judgment.
-
E.
Dila
Dila is the commonly used short name for FC Dila Gori, a professional football club based in Gori, Georgia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd87dcfbc8190b264062002bfe4ba |
completed | March 7, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af90817f8c81908c3792bd406c5ce6 |
completed | March 10, 2026, 3:31 a.m. |
Created at: March 6, 2026, 9:50 p.m.