Triple

T17285203

Position	Surface form	Disambiguated ID	Type / Status
Subject	Fragrant Hills Park	`E419635`	entity
Predicate	ChineseName	`P744`	FINISHED
Object	香山公园香山公园 is a historic imperial garden and popular scenic park in Beijing, famed for its wooded hills, autumn foliage, and traditional Chinese pavilions and temples.	`E1260580`	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: 香山公园 | Statement: [Fragrant Hills Park, ChineseName, 香山公园]

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07

Target entity: 香山公园
Context triple: [Fragrant Hills Park, ChineseName, 香山公园]

A. 景山
景山 is a historic artificial hill and scenic park located just north of the Forbidden City in central Beijing, China.
B. 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。
C. 地坛公园
地坛公园是位于北京市东城区、以明清祭地坛遗址为核心的历史文化公园和城市绿地。
D. 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。
E. 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。
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: 香山公园
Triple: [Fragrant Hills Park, ChineseName, 香山公园]

Generated description

香山公园 is a historic imperial garden and popular scenic park in Beijing, famed for its wooded hills, autumn foliage, and traditional Chinese pavilions and temples.

NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07

Target entity: 香山公园
Target entity description: 香山公园 is a historic imperial garden and popular scenic park in Beijing, famed for its wooded hills, autumn foliage, and traditional Chinese pavilions and temples.

A. 景山
景山 is a historic artificial hill and scenic park located just north of the Forbidden City in central Beijing, China.
B. 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。
C. 地坛公园
地坛公园是位于北京市东城区、以明清祭地坛遗址为核心的历史文化公园和城市绿地。
D. 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。
E. 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。
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_69d886da626481908a14ce7830329a35`	completed	April 10, 2026, 5:12 a.m.
NER	Named-entity recognition	`batch_69e4332cabdc8190bbc711ab806d53bf`	completed	April 19, 2026, 1:43 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a017955448481909c2464a14c2a9799`	completed	May 11, 2026, 6:38 a.m.
NEDg	Description generation	`batch_6a017a193f6881908f39596cb235111f`	completed	May 11, 2026, 6:41 a.m.
NED2	Entity disambiguation (via description)	`batch_6a017b5045d08190b7c7409960f1438c`	completed	May 11, 2026, 6:46 a.m.

Created at: April 10, 2026, 5:40 a.m.