Triple
T2140726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghan American |
E46753
|
entity |
| Predicate | language |
P15
|
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 American, language, Dari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dari Context triple: [Afghan American, language, 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.
Adad
Adad is the Mesopotamian storm and rain god, associated with thunder, fertility, and divine judgment.
-
D.
Dila
Dila is the commonly used short name for FC Dila Gori, a professional football club based in Gori, Georgia.
-
E.
Sana'i
Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbe04135c8190ab100b4b3879cb01 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58d5535c8190b59293afe3a10834 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:44 p.m.