Triple
T17749518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riding Alone for Thousands of Miles |
E443075
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Meng Peicong
Meng Peicong is a film editor known for working on the Chinese drama film "Riding Alone for Thousands of Miles."
|
E1368718
|
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: Meng Peicong | Statement: [Riding Alone for Thousands of Miles, editedBy, Meng Peicong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meng Peicong Context triple: [Riding Alone for Thousands of Miles, editedBy, Meng Peicong]
-
A.
He Mengxiong
He Mengxiong was a Chinese military officer and revolutionary associated with early 20th-century nationalist movements.
-
B.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
-
C.
Zhu Peide
Zhu Peide was a Chinese Nationalist military general and politician who held senior command and governmental roles during the Republic of China era.
-
D.
Liu Bingzhong
Liu Bingzhong was a prominent Yuan dynasty scholar-official, architect, and urban planner best known for helping design the Mongol capital that became Beijing.
-
E.
Wang Xiancheng
Wang Xiancheng was a Ming dynasty official and scholar best known for creating the renowned classical Chinese landscape garden now called the Humble Administrator's Garden in Suzhou.
- 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: Meng Peicong Triple: [Riding Alone for Thousands of Miles, editedBy, Meng Peicong]
Generated description
Meng Peicong is a film editor known for working on the Chinese drama film "Riding Alone for Thousands of Miles."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meng Peicong Target entity description: Meng Peicong is a film editor known for working on the Chinese drama film "Riding Alone for Thousands of Miles."
-
A.
He Mengxiong
He Mengxiong was a Chinese military officer and revolutionary associated with early 20th-century nationalist movements.
-
B.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
-
C.
Zhu Peide
Zhu Peide was a Chinese Nationalist military general and politician who held senior command and governmental roles during the Republic of China era.
-
D.
Liu Bingzhong
Liu Bingzhong was a prominent Yuan dynasty scholar-official, architect, and urban planner best known for helping design the Mongol capital that became Beijing.
-
E.
Wang Xiancheng
Wang Xiancheng was a Ming dynasty official and scholar best known for creating the renowned classical Chinese landscape garden now called the Humble Administrator's Garden in Suzhou.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48418c0188190beb31809b40e4648 |
completed | April 19, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0714355ec081909a1387b65749d627 |
completed | May 15, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_6a0714d428c88190b84f70042cf90312 |
completed | May 15, 2026, 12:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0715a8888081908d3009e19b1c7c2f |
completed | May 15, 2026, 12:46 p.m. |
Created at: April 10, 2026, 10:10 a.m.