Triple

T26902301
Position Surface form Disambiguated ID Type / Status
Subject 建邺区 E678064 entity
Predicate hasPinyinName P2508 FINISHED
Object Jianye Qu
Jianye Qu is a district of Nanjing in Jiangsu Province, China, known for its modern urban development and location along the Yangtze River.
E1746775 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: Jianye Qu | Statement: [建邺区, hasPinyinName, Jianye Qu]
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: Jianye Qu
Triple: [建邺区, hasPinyinName, Jianye Qu]
Generated description
Jianye Qu is a district of Nanjing in Jiangsu Province, China, known for its modern urban development and location along the Yangtze River.

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_69eee9befee48190a26f214faa867be7 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61fb05f8c819098c801df80e58551 completed May 2, 2026, 4 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121eaa66688190afb61b4865d8a86d completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121fcbbfa88190920877882c038ac8 completed May 23, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a12205e89f4819098a8901d520e9c7d completed May 23, 2026, 9:47 p.m.
Created at: April 27, 2026, 5:51 a.m.