Triple

T30219087
Position Surface form Disambiguated ID Type / Status
Subject 重庆轨道交通 E768289 entity
Predicate notableStation P3858 FINISHED
Object 李子坝站
李子坝站是重庆轨道交通中因列车穿楼而过的独特高架车站，以其壮观的城市景观和网红打卡地位而闻名。
 E1903154 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: 李子坝站 | Statement: [重庆轨道交通, notableStation, 李子坝站]
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: 李子坝站
Triple: [重庆轨道交通, notableStation, 李子坝站]
Generated description
李子坝站是重庆轨道交通中因列车穿楼而过的独特高架车站，以其壮观的城市景观和网红打卡地位而闻名。

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_69f2247fd8b8819087fcf83cb7a05eb8 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ff800788190b72b805d7ab44594 completed May 2, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2758efddf08190ae9b43152cc65e14 completed June 9, 2026, 12:06 a.m.
NEDg Description generation batch_6a275a8244788190837ad72957f937db completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275b97a8b081909b579bb004a94f75 completed June 9, 2026, 12:17 a.m.
Created at: April 29, 2026, 7:34 p.m.