Triple
T14004087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Han |
E336901
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Wu Han |
E336901
|
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: Wu Han | Statement: [Wu Han, name, Wu Han]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wu Han Context triple: [Wu Han, name, Wu Han]
-
A.
Wu Han
chosen
Wu Han was a prominent Chinese historian and politician whose critical play about a Ming dynasty official became a key trigger for the Cultural Revolution.
-
B.
Cao Yan
Cao Yan was a lesser-known member of the Cao Wei imperial clan during China’s Three Kingdoms period, recognized primarily for his adoption by the Wei emperor Cao Rui.
-
C.
Zhao Xiaoding
Zhao Xiaoding is a Chinese cinematographer best known for his visually striking work on major films such as "House of Flying Daggers" and other collaborations with director Zhang Yimou.
-
D.
Wen Yuansheng
Wen Yuansheng is a Chinese entrepreneur best known for founding Sany Heavy Industry, one of the world’s leading construction machinery manufacturers.
-
E.
Song Shilun
Song Shilun was a prominent Chinese general of the People’s Volunteer Army during the Korean War, noted for leading Chinese forces in major campaigns against United Nations troops.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed1d2548190bb46d6b7cba4ffde |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc329891c8190b4dcb9913e235a1c |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.