Triple

T32236006
Position Surface form Disambiguated ID Type / Status
Subject Shanghai urban public transport network E823466 entity
Predicate connectsTo P845 FINISHED
Object Shanghai West Railway Station
Shanghai West Railway Station is a major railway and transportation hub in Shanghai that serves regional and long-distance trains and integrates with the city’s urban transit network.
E2003212 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: Shanghai West Railway Station | Statement: [Shanghai urban public transport network, connectsTo, Shanghai West Railway Station]
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: Shanghai West Railway Station
Triple: [Shanghai urban public transport network, connectsTo, Shanghai West Railway Station]
Generated description
Shanghai West Railway Station is a major railway and transportation hub in Shanghai that serves regional and long-distance trains and integrates with the city’s urban transit network.

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_69f3490c140481908ed53b98b561eaa1 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bbfe2bc88190a36ce3d7230d74a4 completed May 3, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a33e88cec1081908382d5c42b578410 completed June 18, 2026, 12:46 p.m.
NEDg Description generation batch_6a33e9686bd08190a0e2e705670ce6ea completed June 18, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_6a341e5c4ad88190b278ef9dbf9ac3a2 completed June 18, 2026, 4:35 p.m.
Created at: May 1, 2026, 12:39 a.m.