Triple

T27968208
Position Surface form Disambiguated ID Type / Status
Subject Baiyun Mountain E704782 entity
Predicate hasChineseName P4878 FINISHED
Object 白云山
白云山是位于中国广东省广州市北部的一座著名风景名山,以山峦叠翠、云雾缭绕和城市观景胜地而闻名。
E1796050 NE FINISHED

How this triple was built (2 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: 白云山 | Statement: [Baiyun Mountain, hasChineseName, 白云山]
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: 白云山
Triple: [Baiyun Mountain, hasChineseName, 白云山]
Generated description
白云山是位于中国广东省广州市北部的一座著名风景名山,以山峦叠翠、云雾缭绕和城市观景胜地而闻名。

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_69ef841061e48190b5570f9562f7434d completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63b3337748190ae03ce1742a31d22 completed May 2, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1311731ffc819097a323a325b007dc completed May 24, 2026, 2:55 p.m.
NEDg Description generation batch_6a1313431f9c8190a4ee1c50f1428a70 completed May 24, 2026, 3:03 p.m.
NED2 Entity disambiguation (via description) batch_6a13141302b48190be6929fdd41bde62 completed May 24, 2026, 3:06 p.m.
Created at: April 27, 2026, 7:36 p.m.