Triple
T9889202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese opera |
E181412
|
entity |
| Predicate | hasCharacterType |
P10724
|
FINISHED |
| Object | sheng |
E685460
|
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: sheng | Statement: [Chinese opera, hasCharacterType, sheng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: sheng Context triple: [Chinese opera, hasCharacterType, sheng]
-
A.
sheng
The sheng is a traditional Chinese mouth-blown free reed instrument made of vertical bamboo pipes, known for producing rich, organ-like harmonies.
-
B.
shengyuan
Shengyuan was the lowest scholarly degree in imperial China’s examination system, designating entry-level licentiates eligible for further civil service exams.
-
C.
Sheng
chosen
Sheng is the primary male role type in traditional Chinese Peking opera, typically portraying dignified scholars, officials, and heroic figures.
-
D.
Sheng
Sheng is an urban Kenyan slang language that blends Swahili, English, and various local languages, widely spoken in Nairobi’s informal settlements and youth culture.
-
E.
Shengzhi
Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb47be2988190811a99dc56ae542a |
completed | April 2, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb08075c81908e017df8048daba8 |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:39 p.m.