Triple
T21685649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turanian army |
E535221
|
entity |
| Predicate | commandedBy |
P1407
|
FINISHED |
| Object | Afrasiab |
—
|
NE NERFINISHED |
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: Afrasiab | Statement: [Turanian army, commandedBy, Afrasiab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Afrasiab Context triple: [Turanian army, commandedBy, Afrasiab]
-
A.
Afrasiab
chosen
Afrasiab is a legendary Turanian king and formidable adversary of Iran in the Persian epic Shahnameh.
-
B.
Tushpa
Tushpa was the ancient fortified city on the eastern shore of Lake Van that served as the political and cultural center of the Kingdom of Urartu in the early first millennium BCE.
-
C.
Sarakhs
Sarakhs is a historic border city in northeastern Iran, known for its strategic location along ancient trade routes between Iran and Central Asia.
-
D.
Khurashan
Khurashan was a Georgian noblewoman known primarily as the wife of King Levan of Kakheti in the 16th century.
-
E.
Agdash
Agdash is a regional city in central Azerbaijan known for its agricultural economy and location near the Kura River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cb69f081908ed0c7ebea429898 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:44 p.m.