Triple

T14987384
Position Surface form Disambiguated ID Type / Status
Subject Grand Paris Express E373739 entity
Predicate hasComponent P35 FINISHED
Object Line 17
Line 17 is a planned automated metro line of the Grand Paris Express project designed to improve rapid transit connections in the Paris metropolitan area.
 E1134371 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 17 | Statement: [Grand Paris Express, hasComponent, Line 17]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 17
Context triple: [Grand Paris Express, hasComponent, Line 17]
  • A. Line 17
    Line 17 is a suburban rapid transit line of the Shanghai Metro that primarily serves the western districts of the city, connecting urban Shanghai with outlying residential and developing areas.
  • B. Line 17
    Line 17 is a rapid transit line of the Beijing Subway system designed to improve north–south connectivity across the city.
  • C. Line 18
    Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • D. Line 18
    Line 18 is a rapid transit line of the Shanghai Metro system serving various districts in Shanghai, China.
  • E. Line 18
    Line 18 is a planned rapid transit line of the Chongqing Metro system in Chongqing, 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 17
Triple: [Grand Paris Express, hasComponent, Line 17]
Generated description
Line 17 is a planned automated metro line of the Grand Paris Express project designed to improve rapid transit connections in the Paris metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 17
Target entity description: Line 17 is a planned automated metro line of the Grand Paris Express project designed to improve rapid transit connections in the Paris metropolitan area.
  • A. Line 17
    Line 17 is a rapid transit line of the Beijing Subway system designed to improve north–south connectivity across the city.
  • B. Line 17
    Line 17 is a suburban rapid transit line of the Shanghai Metro that primarily serves the western districts of the city, connecting urban Shanghai with outlying residential and developing areas.
  • C. Line 18
    Line 18 is a rapid transit line of the Shanghai Metro system serving various districts in Shanghai, China.
  • D. Line 18
    Line 18 is a planned rapid transit line of the Chongqing Metro system in Chongqing, China.
  • E. Line 18
    Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, 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_69fe9dc625888190bf98eecf5f5b6707 completed May 9, 2026, 2:36 a.m.
NEDg Description generation batch_69fea1f203a48190a9cd007727ffb5be completed May 9, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69fea27494ec8190ac6b796b12655624 completed May 9, 2026, 2:56 a.m.
Created at: April 10, 2026, 2:53 a.m.