Triple
T12148866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Game of Death |
E289399
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Si wang you xi
Si wang you xi is the Chinese title of the 1978 martial arts film "Game of Death," famously featuring Bruce Lee.
|
E964062
|
NE FINISHED |
How this triple was built (4 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: Si wang you xi | Statement: [Game of Death, alsoKnownAs, Si wang you xi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Si wang you xi Context triple: [Game of Death, alsoKnownAs, Si wang you xi]
-
A.
XiRonga
XiRonga is a Bantu language spoken primarily by the Ronga people in southern Mozambique and surrounding regions.
-
B.
Xierqi
Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
-
C.
Xixiabangma
Xixiabangma is an 8,000-meter-class mountain in the Himalayas of Tibet, known as one of the world’s fourteen highest peaks.
-
D.
Xiadu
Xiadu was an ancient Chinese city that served as a major political and cultural center of the Warring States–period Yan kingdom.
-
E.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Si wang you xi Triple: [Game of Death, alsoKnownAs, Si wang you xi]
Generated description
Si wang you xi is the Chinese title of the 1978 martial arts film "Game of Death," famously featuring Bruce Lee.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Si wang you xi Target entity description: Si wang you xi is the Chinese title of the 1978 martial arts film "Game of Death," famously featuring Bruce Lee.
-
A.
XiRonga
XiRonga is a Bantu language spoken primarily by the Ronga people in southern Mozambique and surrounding regions.
-
B.
Xierqi
Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
-
C.
Xixiabangma
Xixiabangma is an 8,000-meter-class mountain in the Himalayas of Tibet, known as one of the world’s fourteen highest peaks.
-
D.
Xiadu
Xiadu was an ancient Chinese city that served as a major political and cultural center of the Warring States–period Yan kingdom.
-
E.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
- F. None of above. chosen
Provenance (5 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915ad6ef08190b334a97d6ab41487 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f698c5648190a5a29e08f2b7d8ab |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f5fed2d57881908103ce89a365cdd4 |
completed | May 2, 2026, 1:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f600bcaf288190b6204f985d3be638 |
completed | May 2, 2026, 1:48 p.m. |
Created at: April 8, 2026, 9:49 p.m.