Triple
T17460093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese People's Volunteer Army |
E425128
|
entity |
| Predicate | commander |
P1061
|
FINISHED |
| Object | Deng Hua |
—
|
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: Deng Hua | Statement: [Chinese People's Volunteer Army, commander, Deng Hua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deng Hua Context triple: [Chinese People's Volunteer Army, commander, Deng Hua]
-
A.
Deng Hua
chosen
Deng Hua was a prominent Chinese military commander and general in the People's Volunteer Army during the Korean War.
-
B.
Deng Yan
Deng Yan is a fictional character played by actress Natasha Liu Bordizzo, best known from the Star Wars series "Ahsoka."
-
C.
Deng Wenge
Deng Wenge, better known as Wendi Deng, is a Chinese-American businesswoman and film producer widely recognized as the former wife of media mogul Rupert Murdoch.
-
D.
Deng Wenge
Deng Wenge is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
E.
Deng Xiansheng
Deng Xiansheng is the birth name of Deng Xiaoping, the paramount Chinese leader who led major economic reforms and opening-up policies in the late 20th century.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a3031c8190ab1dd0d41b002dd2 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.