Triple
T20144183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Han Dejun |
E491257
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Han Dejun |
—
|
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: Han Dejun | Statement: [Han Dejun, name, Han Dejun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Han Dejun Context triple: [Han Dejun, name, Han Dejun]
-
A.
Han Dejun
chosen
Han Dejun is a prominent Chinese professional basketball center known for his long-time impact and leadership with the Liaoning Flying Leopards in the CBA.
-
B.
Han Tiefang
Han Tiefang is a key figure in the Crane-Iron wuxia novel series, known for his involvement in the intricate martial-arts conflicts and family sagas that drive the story.
-
C.
Jun Yu
Jun Yu is an actor known for his role in Disney's live-action adaptation of "Mulan" (2020).
-
D.
Hao Haidong
Hao Haidong is a former Chinese footballer widely regarded as one of China's greatest strikers and all-time leading scorers for both club and country.
-
E.
Zheng Dongguo
Zheng Dongguo was a prominent Nationalist Chinese general best known for his leadership in key campaigns during the Second Sino-Japanese War and the Chinese Civil War.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679d89688190ae88d81002d16d6e |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.