Triple
T8681657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feng |
E206051
|
entity |
| Predicate | transliteratesCharacter |
P84461
|
FINISHED |
| Object | 豐 |
E206051
|
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: 豐 | Statement: [Feng, transliteratesCharacter, 豐]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 豐 Context triple: [Feng, transliteratesCharacter, 豐]
-
A.
陳
陳 is a common Chinese surname and character with historical roots, widely used across Chinese-speaking communities and often romanized as "Chan," "Chen," or similar variants.
-
B.
Feng
chosen
Feng is a Chinese surname borne by various notable figures in Chinese history and culture.
-
C.
Feng
Feng was an early capital city of the Zhou dynasty in ancient China, serving as a key political and cultural center before later relocations.
-
D.
Yuanfu
Yuanfu was the courtesy name of Lin Zexu, the prominent Qing dynasty official known for his role in suppressing the opium trade and helping trigger the First Opium War.
-
E.
Zeng
Zeng is a Chinese surname and given name commonly rendered in pinyin and borne by numerous historical and contemporary figures in China.
- 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_69ca835379688190aa06b9d98e684d58 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c2e9c688190aceefaa2c3b7d7bd |
completed | March 31, 2026, 11:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3b9fb848190b7126f8f6a1ba76f |
completed | April 2, 2026, 10:54 p.m. |
Created at: March 30, 2026, 6:32 p.m.