Triple
T23408562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guangxu Emperor |
E560001
|
entity |
| Predicate | personalName |
P24312
|
FINISHED |
| Object | Zaitian |
—
|
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: Zaitian | Statement: [Guangxu Emperor, personalName, Zaitian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaitian Context triple: [Guangxu Emperor, personalName, Zaitian]
-
A.
Zaitian
chosen
Zaitian was the personal name of the Guangxu Emperor, a late Qing dynasty ruler of China known for his attempted modernization reforms and his confinement under Empress Dowager Cixi.
-
B.
Tajuan
Tajuan is the given first name of former NFL cornerback Ty Law.
-
C.
Aimaq
Aimaq are a Persian-speaking, traditionally semi-nomadic ethnic group primarily inhabiting western and central Afghanistan and parts of eastern Iran.
-
D.
Shihezi
Shihezi is a modern, planned city in northern Xinjiang, China, known as an important agricultural and industrial hub in the region.
-
E.
Kaidu
Kaidu was a 13th-century Mongol prince and powerful rival of Kublai Khan who led prolonged resistance against the Yuan dynasty in Central Asia.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50fff10819094e71fb0c11b7d95 |
completed | April 29, 2026, 6:28 a.m. |
Created at: April 17, 2026, 5:38 p.m.