Triple
T11716285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mummy: Tomb of the Dragon Emperor |
E278505
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Jet Li as Emperor Han |
E296891
|
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: Jet Li as Emperor Han | Statement: [The Mummy: Tomb of the Dragon Emperor, characterPortrayed, Jet Li as Emperor Han]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jet Li as Emperor Han Context triple: [The Mummy: Tomb of the Dragon Emperor, characterPortrayed, Jet Li as Emperor Han]
-
A.
Chow Yun-fat as the Monk
Chow Yun-fat as the Monk is the wise, ageless Tibetan warrior-monk protagonist of the action-comedy film "Bulletproof Monk," who protects a powerful ancient scroll while mentoring an unlikely successor.
-
B.
Jet Li
chosen
Jet Li is a Chinese-born martial artist and actor renowned for his high-impact roles in Hong Kong and Hollywood action films such as "Once Upon a Time in China," "Fist of Legend," and "Hero."
-
C.
Daniel Wu as Lu Ren
Daniel Wu as Lu Ren is a rugged ship captain and ally who helps Lara Croft on her perilous expedition in the 2018 film "Tomb Raider."
-
D.
Lin Sen
Lin Sen was a Chinese politician who served as the chairman of the National Government of the Republic of China during the turbulent years leading up to and including much of the Second Sino-Japanese War.
-
E.
Jimmy Lei Ba
Jimmy Lei Ba is a machine learning researcher known for influential contributions to deep learning optimization and normalization techniques, including the development of Layer Normalization.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c10d988190842acd824135cf15 |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83a9479c81909cbe63d81255a1bf |
completed | April 27, 2026, 3:41 p.m. |
Created at: April 8, 2026, 9:40 p.m.