Triple
T8522471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Century Park |
E201724
|
entity |
| Predicate | ChineseName |
P744
|
FINISHED |
| Object |
世纪公园
世纪公园是位于中国上海浦东新区的一座大型城市综合公园,以广阔的绿地、湖泊和休闲设施著称。
|
E738031
|
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: 世纪公园 | Statement: [Century Park, ChineseName, 世纪公园]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 世纪公园 Context triple: [Century Park, ChineseName, 世纪公园]
-
A.
外滩
外滩是位于中国上海黄浦江西岸、以万国建筑群和城市天际线景观著称的历史性滨水区域与著名旅游地标。
-
B.
Weiwuying Metropolitan Park
Weiwuying Metropolitan Park is a large urban green space in Kaohsiung, Taiwan, known for its expansive lawns, recreational facilities, and integration with the nearby Weiwuying National Kaohsiung Center for the Arts.
-
C.
Lujiazui Central Green Space
Lujiazui Central Green Space is a large urban park and landscaped open area in Shanghai’s Lujiazui financial district, offering greenery, water features, and recreational space amid the surrounding skyscrapers.
-
D.
Changfeng Park
Changfeng Park is a large urban park in Shanghai known for its lakes, green spaces, and recreational facilities.
-
E.
Fuxing Park
Fuxing Park is a historic European-style public park in Shanghai known for its landscaped gardens, open plazas, and lively local social scene.
- 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: 世纪公园 Triple: [Century Park, ChineseName, 世纪公园]
Generated description
世纪公园是位于中国上海浦东新区的一座大型城市综合公园,以广阔的绿地、湖泊和休闲设施著称。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 世纪公园 Target entity description: 世纪公园是位于中国上海浦东新区的一座大型城市综合公园,以广阔的绿地、湖泊和休闲设施著称。
-
A.
外滩
外滩是位于中国上海黄浦江西岸、以万国建筑群和城市天际线景观著称的历史性滨水区域与著名旅游地标。
-
B.
Weiwuying Metropolitan Park
Weiwuying Metropolitan Park is a large urban green space in Kaohsiung, Taiwan, known for its expansive lawns, recreational facilities, and integration with the nearby Weiwuying National Kaohsiung Center for the Arts.
-
C.
Lujiazui Central Green Space
Lujiazui Central Green Space is a large urban park and landscaped open area in Shanghai’s Lujiazui financial district, offering greenery, water features, and recreational space amid the surrounding skyscrapers.
-
D.
Changfeng Park
Changfeng Park is a large urban park in Shanghai known for its lakes, green spaces, and recreational facilities.
-
E.
Fuxing Park
Fuxing Park is a historic European-style public park in Shanghai known for its landscaped gardens, open plazas, and lively local social scene.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe64215408190b45f462a32d3471d |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e8399f481909992aedf0d918cbc |
completed | April 2, 2026, 11:09 a.m. |
| NEDg | Description generation | batch_69ce4ffcf7488190b94cae18be14e8ff |
completed | April 2, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce507766448190830dd3efc8a79a74 |
completed | April 2, 2026, 11:18 a.m. |
Created at: March 30, 2026, 6:16 p.m.