Triple
T16583620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qimen |
E402897
|
entity |
| Predicate | hasChineseName |
P4878
|
FINISHED |
| Object |
祁门
祁门是位于中国安徽省南部黄山市下辖的一个县，以出产著名的祁门红茶而闻名。
|
E1220960
|
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: 祁门 | Statement: [Qimen, hasChineseName, 祁门]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 祁门 Context triple: [Qimen, hasChineseName, 祁门]
-
A.
霍山县
霍山县是位于中国安徽省西部大别山腹地、以生态旅游和茶叶等特色农业闻名的山区县。
-
B.
六安
六安 is a prefecture-level city in western Anhui Province, China, known for its rich history and famous Lu'an Melon Seed tea.
-
C.
金寨县
金寨县是位于中国安徽省西部、大别山腹地的一个山区县，以革命老区和红色旅游资源闻名。
-
D.
舒城县
舒城县 is a county under the administration of Lu’an City in Anhui Province, eastern China, known for its agricultural economy and location in the Dabie Mountain region.
-
E.
马鞍山
马鞍山是位于中国安徽省东部、长江沿岸的一座以钢铁工业和山水景观著称的地级市。
- 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: 祁门 Triple: [Qimen, hasChineseName, 祁门]
Generated description
祁门是位于中国安徽省南部黄山市下辖的一个县，以出产著名的祁门红茶而闻名。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 祁门 Target entity description: 祁门是位于中国安徽省南部黄山市下辖的一个县，以出产著名的祁门红茶而闻名。
-
A.
霍山县
霍山县是位于中国安徽省西部大别山腹地、以生态旅游和茶叶等特色农业闻名的山区县。
-
B.
六安
六安 is a prefecture-level city in western Anhui Province, China, known for its rich history and famous Lu'an Melon Seed tea.
-
C.
金寨县
金寨县是位于中国安徽省西部、大别山腹地的一个山区县，以革命老区和红色旅游资源闻名。
-
D.
舒城县
舒城县 is a county under the administration of Lu’an City in Anhui Province, eastern China, known for its agricultural economy and location in the Dabie Mountain region.
-
E.
马鞍山
马鞍山是位于中国安徽省东部、长江沿岸的一座以钢铁工业和山水景观著称的地级市。
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35999f80c8190852fd4137bc45a80 |
completed | April 18, 2026, 10:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ef2d6048190954144ab848760ec |
completed | May 10, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_6a006fc84390819083d9d2ac1c558827 |
completed | May 10, 2026, 11:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007068715c8190914ccac7b14103e4 |
completed | May 10, 2026, 11:47 a.m. |
Created at: April 10, 2026, 5:16 a.m.