Triple
T15106999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khusrav |
E360812
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Khosru |
E1140973
|
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: Khosru | Statement: [Khusrav, hasVariant, Khosru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khosru Context triple: [Khusrav, hasVariant, Khosru]
-
A.
Khusrau
chosen
Khusrau is a Persian given name historically borne by several notable rulers and cultural figures across the Iranian and broader Middle Eastern world.
-
B.
Khosrowshahi
Khosrowshahi is a Persian surname most prominently associated with Dara Khosrowshahi, the Iranian-American business executive and CEO of Uber.
-
C.
Khusrav
Khusrav is a masculine given name of Persian origin, historically borne by princes and notable figures in Central and South Asia.
-
D.
Kay Khosrow
Kay Khosrow is a legendary, just, and spiritually enlightened king of Iran in Ferdowsi’s epic Shahnameh, renowned for avenging his father and then renouncing his throne to vanish mysteriously.
-
E.
Shahpur
Shahpur is a notable town in Bihar, India, recognized as one of the main urban centers of Bhojpur district.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058af8988190977d998f85893836 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef61cf80819096a3cb611f5af9fc |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:05 a.m.