Triple
T11399292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CRH2 EMU |
E270063
|
entity |
| Predicate | marketedAs |
P1395
|
FINISHED |
| Object |
Hexie Hao
Hexie Hao is a series of high-speed electric multiple unit trains used in China’s railway network, known for operating many of the country’s major high-speed services.
|
E923679
|
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: Hexie Hao | Statement: [CRH2 EMU, marketedAs, Hexie Hao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hexie Hao Context triple: [CRH2 EMU, marketedAs, Hexie Hao]
-
A.
Hao
Hao is a large coral atoll in French Polynesia’s Tuamotu Archipelago, known historically as a strategic Pacific military and logistics base.
-
B.
Hao
Hao was an ancient Chinese city that served as an early capital of the Zhou dynasty.
-
C.
Xianheng
Xianheng was a Chinese imperial era name used during the reign of Emperor Gaozong of the Tang dynasty.
-
D.
Xiaobo
Xiaobo is the given name of Liu Xiaobo, the Chinese literary critic, human rights activist, and Nobel Peace Prize laureate.
-
E.
Xiao Hua
Xiao Hua is best known as the former wife of acclaimed Chinese film director Zhang Yimou.
- 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: Hexie Hao Triple: [CRH2 EMU, marketedAs, Hexie Hao]
Generated description
Hexie Hao is a series of high-speed electric multiple unit trains used in China’s railway network, known for operating many of the country’s major high-speed services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hexie Hao Target entity description: Hexie Hao is a series of high-speed electric multiple unit trains used in China’s railway network, known for operating many of the country’s major high-speed services.
-
A.
Hao
Hao is a large coral atoll in French Polynesia’s Tuamotu Archipelago, known historically as a strategic Pacific military and logistics base.
-
B.
Hao
Hao was an ancient Chinese city that served as an early capital of the Zhou dynasty.
-
C.
Xianheng
Xianheng was a Chinese imperial era name used during the reign of Emperor Gaozong of the Tang dynasty.
-
D.
Xiaobo
Xiaobo is the given name of Liu Xiaobo, the Chinese literary critic, human rights activist, and Nobel Peace Prize laureate.
-
E.
Xiao Hua
Xiao Hua is best known as the former wife of acclaimed Chinese film director Zhang Yimou.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001adc188190ae45227856156412 |
completed | April 9, 2026, 7:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58cf75ec08190a571e5178bcde274 |
completed | April 20, 2026, 2:18 a.m. |
| NEDg | Description generation | batch_69e59774e6648190a38b2515a83c2e0c |
completed | April 20, 2026, 3:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5a3abf24481908fb71f4ef6b13532 |
completed | April 20, 2026, 3:55 a.m. |
Created at: April 8, 2026, 9:34 p.m.