Triple

T19444498
Position Surface form Disambiguated ID Type / Status
Subject Maximilian Bittner E486436 entity
Predicate employer P7 FINISHED
Object Lazada Group NE NERFINISHED

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: Lazada Group | Statement: [Maximilian Bittner, employer, Lazada Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lazada Group
Context triple: [Maximilian Bittner, employer, Lazada Group]
  • A. Lazada chosen
    Lazada is a leading Southeast Asian e-commerce platform offering a wide range of products through online marketplaces in multiple countries across the region.
  • B. Shopee
    Shopee is a major Southeast Asian e-commerce platform known for its mobile-first marketplace, wide range of products, and integrated digital payment and logistics services.
  • C. Alibaba.com
    Alibaba.com is a leading global online business-to-business (B2B) marketplace that connects suppliers, primarily manufacturers and wholesalers, with buyers around the world.
  • D. Alibaba Group
    Alibaba Group is a Chinese multinational conglomerate specializing in e-commerce, retail, internet, and technology, best known for operating major online marketplaces like Taobao and Tmall.
  • E. Pinduoduo
    Pinduoduo is a major Chinese e-commerce platform known for its group-buying model and deep discounts that target price-sensitive consumers, especially in lower-tier cities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63387e2048190bfb13fea434ddb46 completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.