Triple
T15864890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coal Hill |
E384685
|
entity |
| Predicate | hasChineseName |
P4878
|
FINISHED |
| Object |
景山
景山 is a historic artificial hill and scenic park located just north of the Forbidden City in central Beijing, China.
|
E1182060
|
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: 景山 | Statement: [Coal Hill, hasChineseName, 景山]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 景山 Context triple: [Coal Hill, hasChineseName, 景山]
-
A.
月坛
月坛是位于北京市西城区、明清时期用于祭月的古代皇家祭坛遗址及现今的城市公园。
-
B.
日坛公园
日坛公园是位于北京市东城区、以明清祭日坛遗址为核心的历史文化公园。
-
C.
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。
-
D.
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。
-
E.
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。
- 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: 景山 Triple: [Coal Hill, hasChineseName, 景山]
Generated description
景山 is a historic artificial hill and scenic park located just north of the Forbidden City in central Beijing, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 景山 Target entity description: 景山 is a historic artificial hill and scenic park located just north of the Forbidden City in central Beijing, China.
-
A.
月坛
月坛是位于北京市西城区、明清时期用于祭月的古代皇家祭坛遗址及现今的城市公园。
-
B.
日坛公园
日坛公园是位于北京市东城区、以明清祭日坛遗址为核心的历史文化公园。
-
C.
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。
-
D.
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。
-
E.
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。
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555e4ee48190a3b27b4ab9bdb1c8 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa945d9808190a65f5182db341393 |
completed | May 9, 2026, 9:38 p.m. |
| NEDg | Description generation | batch_69ffaa8b03048190a3745df8a59fe066 |
completed | May 9, 2026, 9:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffab58e7e481908a13b739e0401b8b |
completed | May 9, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:50 a.m.