Triple
T10322119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tekuder |
E242160
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Kublai Khan |
E25319
|
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: Kublai Khan | Statement: [Tekuder, relative, Kublai Khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kublai Khan Context triple: [Tekuder, relative, Kublai Khan]
-
A.
Kublai Khan
chosen
Kublai Khan was the 13th-century Mongol emperor who founded China’s Yuan dynasty and presided over one of the largest empires in history.
-
B.
Yesün Temür
Yesün Temür was a 14th-century Mongol ruler who served as Great Khan of the Mongol Empire and emperor of the Yuan dynasty in China.
-
C.
Toghon Temür
Toghon Temür was the last emperor of the Yuan dynasty in China, whose troubled reign ended with the dynasty’s collapse and the rise of the Ming.
-
D.
Güyük Khan
Güyük Khan was the third Great Khan of the Mongol Empire, ruling briefly in the 1240s and known for consolidating Mongol authority while facing internal dynastic tensions.
-
E.
Möngke Khan
Möngke Khan was the fourth Great Khan of the Mongol Empire, under whose rule the empire reached its greatest territorial extent and saw major administrative and fiscal reforms.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6cce38c8190bfa0f2fb53ed0065 |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d9b2ad881909f3076f8f9d1b1d3 |
completed | April 9, 2026, 3:31 a.m. |
Created at: April 6, 2026, 11:50 a.m.