Triple

T8601258
Position Surface form Disambiguated ID Type / Status
Subject Line 2 (Shanghai Metro) E203679 entity
Predicate connects P390 FINISHED
Object Lujiazui E189182 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: Lujiazui | Statement: [Line 2 (Shanghai Metro), connects, Lujiazui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lujiazui
Context triple: [Line 2 (Shanghai Metro), connects, Lujiazui]
  • A. Lujiazui chosen
    Lujiazui is Shanghai’s major financial district and futuristic skyline area on the east bank of the Huangpu River, known for its cluster of iconic skyscrapers.
  • B. Wudaokou
    Wudaokou is a bustling neighborhood in Beijing known for its universities, tech companies, and vibrant student nightlife.
  • C. Yizhuang
    Yizhuang is a rapidly developing suburban area in southeastern Beijing known for its economic and technological development zone and growing residential communities.
  • D. Gubeikou
    Gubeikou is a historically significant mountain pass and Great Wall fortification in northern China that has long served as a strategic gateway between the North China Plain and the Mongolian plateau.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46d8ff408190acc7cd8dc99b2689 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8f13f7081908317c1b2d87a51b2 completed April 2, 2026, 5:35 p.m.
Created at: March 30, 2026, 6:24 p.m.