Triple
T4008098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haidian District |
E89575
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Xierqi
Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
|
E406595
|
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: Xierqi | Statement: [Haidian District, contains, Xierqi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xierqi Context triple: [Haidian District, contains, Xierqi]
-
A.
Qiying
Qiying was a Qing dynasty statesman and diplomat who played a key role in negotiating several unequal treaties with Western powers in the mid-19th century.
-
B.
Shaoqi
Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
-
C.
Yingqin
Yingqin is the given name of He Yingqin, a prominent Chinese Nationalist military leader and politician of the early 20th century.
-
D.
Yingtian
Yingtian was an important early Ming dynasty capital city, historically centered around present-day Nanjing in China.
-
E.
Qichao
Qichao is the given name of Liang Qichao, a prominent late Qing and early Republican Chinese scholar, journalist, and reformist thinker.
- 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: Xierqi Triple: [Haidian District, contains, Xierqi]
Generated description
Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xierqi Target entity description: Xierqi is a major technology and business hub in Beijing, known for its concentration of high-tech companies and convenient transportation links.
-
A.
Qiying
Qiying was a Qing dynasty statesman and diplomat who played a key role in negotiating several unequal treaties with Western powers in the mid-19th century.
-
B.
Shaoqi
Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of China.
-
C.
Yingqin
Yingqin is the given name of He Yingqin, a prominent Chinese Nationalist military leader and politician of the early 20th century.
-
D.
Yingtian
Yingtian was an important early Ming dynasty capital city, historically centered around present-day Nanjing in China.
-
E.
Qichao
Qichao is the given name of Liang Qichao, a prominent late Qing and early Republican Chinese scholar, journalist, and reformist thinker.
- 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa647f80819081180eb267f1cfcc |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c6ae0ec819099c229a4cfe926f2 |
completed | March 14, 2026, 11:54 a.m. |
| NEDg | Description generation | batch_69b54d41fa008190972411203c8a07f2 |
completed | March 14, 2026, 11:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b54de8dc708190b83978b15aed2e13 |
completed | March 14, 2026, noon |
Created at: March 9, 2026, 3:34 p.m.