Triple

T27897537
Position Surface form Disambiguated ID Type / Status
Subject Shuangcheng District E705534 entity
Predicate hasChineseName P4878 FINISHED
Object 双城区
双城区是中国黑龙江省哈尔滨市下辖的一个市辖区，以农业和食品加工业为特色。
 E1793546 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: 双城区 | Statement: [Shuangcheng District, hasChineseName, 双城区]
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: 双城区
Triple: [Shuangcheng District, hasChineseName, 双城区]
Generated description
双城区是中国黑龙江省哈尔滨市下辖的一个市辖区，以农业和食品加工业为特色。

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_69ef96b490ac8190a412d04c5d009f3e completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f639f5d2588190b87fdb14a487d9d8 completed May 2, 2026, 5:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a130364ce5c81909baa63dcb87ff497 completed May 24, 2026, 1:55 p.m.
NEDg Description generation batch_6a13044829448190905f994a78ac7871 completed May 24, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_6a130515074c81909e402d00ce95b85f completed May 24, 2026, 2:03 p.m.
Created at: April 27, 2026, 6:39 p.m.