Triple

T8375666
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou–Shenzhen–Hong Kong Express Rail Link E197567 entity
Predicate alsoKnownAs P39 FINISHED
Object XRL
XRL is a high-speed rail line connecting Guangzhou, Shenzhen, and Hong Kong, forming a key part of China’s national high-speed railway network.
 E729712 NE FINISHED

How this triple was built (4 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: XRL | Statement: [Guangzhou–Shenzhen–Hong Kong Express Rail Link, alsoKnownAs, XRL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XRL
Context triple: [Guangzhou–Shenzhen–Hong Kong Express Rail Link, alsoKnownAs, XRL]
  • A. XRX
    XRX is the stock ticker symbol for Xerox Holdings Corporation, an American company known for its document management technologies and printing solutions.
  • B. Xelb
    Xelb is the former Arabic name for the Portuguese city of Silves, a historically significant town in the Algarve region.
  • C. l’X
    l’X is the traditional nickname of École Polytechnique, France’s elite engineering grande école renowned for its rigorous scientific education and prestigious alumni.
  • D. XHP
    XHP is the IATA station code assigned to Paris's Gare de l'Est railway station.
  • E. XHP
    XHP is a PHP extension for Facebook's Hack language that lets developers write XML-like syntax directly in code to create robust, type-safe user interface components.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: XRL
Triple: [Guangzhou–Shenzhen–Hong Kong Express Rail Link, alsoKnownAs, XRL]
Generated description
XRL is a high-speed rail line connecting Guangzhou, Shenzhen, and Hong Kong, forming a key part of China’s national high-speed railway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XRL
Target entity description: XRL is a high-speed rail line connecting Guangzhou, Shenzhen, and Hong Kong, forming a key part of China’s national high-speed railway network.
  • A. XRX
    XRX is the stock ticker symbol for Xerox Holdings Corporation, an American company known for its document management technologies and printing solutions.
  • B. Xelb
    Xelb is the former Arabic name for the Portuguese city of Silves, a historically significant town in the Algarve region.
  • C. l’X
    l’X is the traditional nickname of École Polytechnique, France’s elite engineering grande école renowned for its rigorous scientific education and prestigious alumni.
  • D. XHP
    XHP is the IATA station code assigned to Paris's Gare de l'Est railway station.
  • E. XHP
    XHP is a PHP extension for Facebook's Hack language that lets developers write XML-like syntax directly in code to create robust, type-safe user interface components.
  • F. None of above. chosen

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_69ca82f56730819080cec5d991c76f4c completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80bf6b8081909b98762b1f900bef completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde7f19ba08190a08cf5aea522c021 completed April 2, 2026, 3:52 a.m.
NEDg Description generation batch_69cdebf944008190b7e758ac59257e22 completed April 2, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69cdeccedf4081909cab853ee1ff1b82 completed April 2, 2026, 4:13 a.m.
Created at: March 30, 2026, 6:01 p.m.