Triple
T12001937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peng Huanwu |
E285685
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Peng Huanwu |
E285685
|
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: Peng Huanwu | Statement: [Peng Huanwu, name, Peng Huanwu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peng Huanwu Context triple: [Peng Huanwu, name, Peng Huanwu]
-
A.
Peng Huanwu
chosen
Peng Huanwu was a prominent Chinese theoretical physicist known for his contributions to nuclear and particle physics and for helping advance modern physics research in China.
-
B.
Xue Rengui
Xue Rengui was a famed Tang dynasty general renowned for his military exploits on the empire’s frontiers, particularly in campaigns against Goguryeo and other neighboring states.
-
C.
Zeng Liansong
Zeng Liansong was a Chinese designer best known for creating the national flag of the People's Republic of China.
-
D.
Wang Zhenghua
Wang Zhenghua is a Chinese entrepreneur best known as the founder of the low-cost carrier Spring Airlines.
-
E.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c36b248190b446b17def94885b |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f66849ba888190a50c5a5fcdb935e0 |
completed | May 2, 2026, 9:10 p.m. |
Created at: April 8, 2026, 9:46 p.m.