Triple

T2212079
Position Surface form Disambiguated ID Type / Status
Subject Geneva public transport network E50939 entity
Predicate hasTrolleybusLine P36816 FINISHED
Object Line 7
Line 7 is a trolleybus route within Geneva’s public transport system that connects key districts of the city.
 E245713 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 7 | Statement: [Geneva public transport network, hasTrolleybusLine, Line 7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 7
Context triple: [Geneva public transport network, hasTrolleybusLine, Line 7]
  • A. Line 7
    Line 7 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • B. Line 7
    Line 7 is one of the main lines of the Tehran Metro rapid transit network, serving various districts of Iran’s capital city.
  • C. Line 7
    Line 7 is an east–west rapid transit line of the Beijing Subway serving several central and southwestern districts of Beijing.
  • D. Line 7
    Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
  • E. Line 7
    Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
  • 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 7
Triple: [Geneva public transport network, hasTrolleybusLine, Line 7]
Generated description
Line 7 is a trolleybus route within Geneva’s public transport system that connects key districts of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 7
Target entity description: Line 7 is a trolleybus route within Geneva’s public transport system that connects key districts of the city.
  • A. Line 7
    Line 7 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • B. Line 7
    Line 7 is an east–west rapid transit line of the Beijing Subway serving several central and southwestern districts of Beijing.
  • C. Line 7
    Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
  • D. Line 7
    Line 7 is one of the main lines of the Tehran Metro rapid transit network, serving various districts of Iran’s capital city.
  • E. Line 7
    Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
  • 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc5b101d48190a321625720d537b6 completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae655245c48190a37f4b6344a9a3dc completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae66579c008190876ce89581337293 completed March 9, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae668ef8bc819085ed1c83f447d396 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:46 p.m.