Triple
T9501570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Xianzong of Tang |
E229152
|
entity |
| Predicate | eraName |
P2938
|
FINISHED |
| Object | Yongzhen |
E793087
|
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: Yongzhen | Statement: [Emperor Xianzong of Tang, eraName, Yongzhen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yongzhen Context triple: [Emperor Xianzong of Tang, eraName, Yongzhen]
-
A.
Yongzhen
chosen
Yongzhen was a brief regnal era during the reign of Emperor Dezong in the late Tang dynasty of China.
-
B.
Daizong
Daizong is the posthumous temple name of the Ming dynasty's Jingtai Emperor, used in ancestral rites and historical records.
-
C.
Kaiyuan
Kaiyuan is a county-level city in Honghe Hani and Yi Autonomous Prefecture in Yunnan Province, southwestern China.
-
D.
Huiguo
Huiguo was a prominent Chinese Buddhist monk of the Tang dynasty and a key master of Esoteric Buddhism who played a crucial role in transmitting these teachings to the Japanese monk Kūkai (Kobo Daishi).
-
E.
Yuanzhen
Yuanzhen was the Chinese era name used during the reign of Temür Khan, the second emperor of the Yuan dynasty.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983d4b708190a4dfef1246986a26 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a10f7b08190b8e4d4bc3b9815c6 |
completed | April 4, 2026, 4:19 p.m. |
Created at: March 30, 2026, 7:57 p.m.