Triple

T14987383
Position Surface form Disambiguated ID Type / Status
Subject Grand Paris Express E373739 entity
Predicate hasComponent P35 FINISHED
Object Line 16
Line 16 is a planned automated metro line in the Grand Paris Express project intended to improve rapid transit connectivity in the eastern suburbs of the Paris metropolitan area.
 E1131484 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: Line 16 | Statement: [Grand Paris Express, hasComponent, Line 16]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 16
Context triple: [Grand Paris Express, hasComponent, Line 16]
  • A. Line 16
    Line 16 is a suburban rapid transit line of the Hangzhou Metro system in Hangzhou, China, connecting the urban network with outlying districts.
  • B. Line 16
    Line 16 is a rapid transit line of the Beijing Subway system serving parts of the city with modern, high-capacity metro service.
  • C. Line 16
    Line 16 is a suburban rapid transit line of the Shanghai Metro that connects central Shanghai with the southeastern outskirts, including the Lingang area.
  • D. Line 16
    Line 16 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China.
  • E. Line 18
    Line 18 is a rapid transit line of the Shanghai Metro system serving various districts in Shanghai, China.
  • 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: Line 16
Triple: [Grand Paris Express, hasComponent, Line 16]
Generated description
Line 16 is a planned automated metro line in the Grand Paris Express project intended to improve rapid transit connectivity in the eastern suburbs of the Paris metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 16
Target entity description: Line 16 is a planned automated metro line in the Grand Paris Express project intended to improve rapid transit connectivity in the eastern suburbs of the Paris metropolitan area.
  • A. Line 16
    Line 16 is a rapid transit line of the Beijing Subway system serving parts of the city with modern, high-capacity metro service.
  • B. Line 16
    Line 16 is a suburban rapid transit line of the Shanghai Metro that connects central Shanghai with the southeastern outskirts, including the Lingang area.
  • C. Line 16
    Line 16 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China.
  • D. Line 16
    Line 16 is a suburban rapid transit line of the Hangzhou Metro system in Hangzhou, China, connecting the urban network with outlying districts.
  • E. Line 18
    Line 18 is a planned rapid transit line of the Chongqing Metro system in Chongqing, China.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7007588819095bb1de029a6f2eb completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969683348190bb4688f24227af88 completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe98a230948190b35e2883475cff33 completed May 9, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_69fe993c6094819086f0de1743272fd4 completed May 9, 2026, 2:17 a.m.
Created at: April 10, 2026, 2:53 a.m.