Triple
T13469866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yunwen |
E311599
|
entity |
| Predicate | templeName |
P44027
|
FINISHED |
| Object | Huidi |
E311600
|
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: Huidi | Statement: [Yunwen, templeName, Huidi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huidi Context triple: [Yunwen, templeName, Huidi]
-
A.
Huidi
chosen
Huidi is the temple name of the Jianwen Emperor, a Ming dynasty ruler known for his short and turbulent reign marked by internal conflict and the usurpation by his uncle, the Yongle Emperor.
-
B.
Xiadu
Xiadu was an ancient Chinese city that served as a major political and cultural center of the Warring States–period Yan kingdom.
-
C.
Sifayuan
Sifayuan is the Mandarin name for Taiwan’s Judicial Yuan, the constitutional body responsible for overseeing the judiciary and interpreting the constitution.
-
D.
Rongji
Rongji is the given name of Zhu Rongji, the former Premier of the People's Republic of China known for his economic reforms and administrative efficiency.
-
E.
Xierqi
Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf21e46081908a00c9acf54f270f |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7547f6b1c8190965b239da0b47e93 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:42 p.m.