Triple

T33406097
Position Surface form Disambiguated ID Type / Status
Subject Anting, China E855441 entity
Predicate hasIndustrialPark P13026 FINISHED
Object Shanghai International Automobile City
Shanghai International Automobile City is a major automotive industry hub and development zone in Anting, Shanghai, focused on car manufacturing, research, and related services.
E2048744 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 International Automobile City | Statement: [Anting, China, hasIndustrialPark, Shanghai International Automobile City]
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 International Automobile City
Triple: [Anting, China, hasIndustrialPark, Shanghai International Automobile City]
Generated description
Shanghai International Automobile City is a major automotive industry hub and development zone in Anting, Shanghai, focused on car manufacturing, research, and related services.

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_69f3496f04a08190804e56ac5098b8e4 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e42fb33081908e8672f30aa3cc03 completed May 3, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3576fabb6881908f22d1fab8ed7e13 completed June 19, 2026, 5:06 p.m.
NEDg Description generation batch_6a35776bbb3c8190bda2a14ef5abdaf8 completed June 19, 2026, 5:07 p.m.
NED2 Entity disambiguation (via description) batch_6a3577e82568819091390ca6df3cf66e completed June 19, 2026, 5:10 p.m.
Created at: May 1, 2026, 1:36 a.m.