Triple

T36520842
Position Surface form Disambiguated ID Type / Status
Subject 顾村公园 E900175 entity
Predicate transportAccess P1288 FINISHED
Object 地铁7号线顾村公园站
地铁7号线顾村公园站是上海轨道交通7号线服务于顾村公园及其周边地区的一座地铁车站。
 E2187617 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: 地铁7号线顾村公园站 | Statement: [顾村公园, transportAccess, 地铁7号线顾村公园站]
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: 地铁7号线顾村公园站
Triple: [顾村公园, transportAccess, 地铁7号线顾村公园站]
Generated description
地铁7号线顾村公园站是上海轨道交通7号线服务于顾村公园及其周边地区的一座地铁车站。

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_69f76e5eedb88190a393b8c623f71dd7 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c213e8448190a27e801d0a69f399 completed May 3, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39dbdfc8208190abf594568c353010 completed June 23, 2026, 1:05 a.m.
NEDg Description generation batch_6a39dd5a787c819089c278f86de8078c completed June 23, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_6a39e17ec0f08190acfb9ec12f86249d completed June 23, 2026, 1:29 a.m.
Created at: May 3, 2026, 4:11 p.m.