Triple
T20933768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubrat |
E515531
|
entity |
| Predicate | hadTitle |
P13335
|
FINISHED |
| Object | khan |
—
|
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: khan | Statement: [Kubrat, hadTitle, khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: khan Context triple: [Kubrat, hadTitle, khan]
-
A.
Khan
chosen
Khan is a common surname of Central and South Asian origin historically associated with nobility and leadership, now widely used across Muslim and other communities worldwide.
-
B.
Khanan
Khanan is the tragic young scholar whose doomed love and spiritual turmoil drive the plot of S. Ansky’s classic Yiddish play "The Dybbuk."
-
C.
Kahn
Kahn is a surname most famously associated with Louis Kahn, the influential 20th-century architect known for his monumental and timeless modernist buildings.
-
D.
Khan Maykr
Khan Maykr is a powerful, godlike ruler of the Maykr race and a major antagonist in Doom Eternal, orchestrating the demonic invasion of Earth.
-
E.
KAHN
KAHN is the ICAO airport code for Athens Ben Epps Airport, a public airport serving Athens, Georgia, in the United States.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f94fc194819099df82357a7f33c7 |
completed | April 21, 2026, 4:13 a.m. |
Created at: April 16, 2026, 12:49 p.m.