Triple
T13823196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 中和殿 |
E332185
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
故宫
故宫是位于北京市中心、以明清皇宫建筑群著称的中国古代皇家宫殿与世界文化遗产。
|
E1063770
|
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: 故宫 | Statement: [中和殿, locatedIn, 故宫]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 故宫 Context triple: [中和殿, locatedIn, 故宫]
-
A.
天安门
天安门是位于北京市中心、作为中国象征性地标和重要政治历史事件发生地的著名城门与广场名称。
-
B.
太庙
太庙是北京故宫东侧一座明清皇家宗庙建筑群,现为对公众开放的历史文化景区。
-
C.
颐和园
颐和园是位于北京市西北部、以宏伟的皇家园林建筑和昆明湖、万寿山自然景观著称的世界文化遗产。
-
D.
午门
午门 is the grand southern entrance and main gate of Beijing’s Forbidden City, historically used for important imperial ceremonies and proclamations.
-
E.
北海公园
北海公园是位于北京市中心、以皇家园林景观和历史文化遗迹著称的大型古典园林公园。
- 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: 故宫 Triple: [中和殿, locatedIn, 故宫]
Generated description
故宫是位于北京市中心、以明清皇宫建筑群著称的中国古代皇家宫殿与世界文化遗产。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 故宫 Target entity description: 故宫是位于北京市中心、以明清皇宫建筑群著称的中国古代皇家宫殿与世界文化遗产。
-
A.
天安门
天安门是位于北京市中心、作为中国象征性地标和重要政治历史事件发生地的著名城门与广场名称。
-
B.
太庙
太庙是北京故宫东侧一座明清皇家宗庙建筑群,现为对公众开放的历史文化景区。
-
C.
颐和园
颐和园是位于北京市西北部、以宏伟的皇家园林建筑和昆明湖、万寿山自然景观著称的世界文化遗产。
-
D.
午门
午门 is the grand southern entrance and main gate of Beijing’s Forbidden City, historically used for important imperial ceremonies and proclamations.
-
E.
北海公园
北海公园是位于北京市中心、以皇家园林景观和历史文化遗迹著称的大型古典园林公园。
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0284428081908043c55caeefb833 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8e60e1c81908d51d723e85e0541 |
completed | May 3, 2026, 9:06 p.m. |
| NEDg | Description generation | batch_69f7b9d81f488190875e9b3f885556ab |
completed | May 3, 2026, 9:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7ba9ba0988190800e685cff4c2186 |
completed | May 3, 2026, 9:14 p.m. |
Created at: April 9, 2026, 10:13 p.m.