Triple

T28547867
Position Surface form Disambiguated ID Type / Status
Subject West Nanjing Road Station E722494 entity
Predicate isMajorAccessPointFor P26211 FINISHED
Object West Nanjing Road shopping area
West Nanjing Road shopping area is a major commercial district in central Shanghai known for its upscale malls, international brand stores, and vibrant urban atmosphere.
E1826762 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: West Nanjing Road shopping area | Statement: [West Nanjing Road Station, isMajorAccessPointFor, West Nanjing Road shopping area]
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: West Nanjing Road shopping area
Triple: [West Nanjing Road Station, isMajorAccessPointFor, West Nanjing Road shopping area]
Generated description
West Nanjing Road shopping area is a major commercial district in central Shanghai known for its upscale malls, international brand stores, and vibrant urban atmosphere.

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_69f01a5e42348190b1ffbca26e739c84 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f6500eddd08190b41c1569f4298f77 completed May 2, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6e2e2b081908fb82a256d6fde65 completed May 31, 2026, 10:32 p.m.
NEDg Description generation batch_6a1cbd32083c8190a839c75d37cb060f completed May 31, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1cbda0a2fc8190972a730b81a629e8 completed May 31, 2026, 11 p.m.
Created at: April 28, 2026, 3:40 a.m.