Triple

T1841558
Position Surface form Disambiguated ID Type / Status
Subject Paris Metro E41186 entity
Predicate hasLine P35 FINISHED
Object Line 4
Line 4 is one of the main north–south lines of the Paris Métro, known for serving central Paris and connecting key railway stations and neighborhoods.
 E211472 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 4 | Statement: [Paris Metro, hasLine, Line 4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 4
Context triple: [Paris Metro, hasLine, Line 4]
  • A. Line 4
    Line 4 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 4
    Line 4 is a major line of the Santiago Metro in Chile, serving key residential and commercial areas in the southeastern part of the city.
  • C. Line 4
    Line 4 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving key urban and suburban areas along its north–south corridor.
  • D. Line 4
    Line 4 is one of the main lines of the Tehran Metro rapid transit system, serving key east–west corridors across Iran’s capital city.
  • E. Line 4
    Line 4 is a circular rapid transit route of the Shanghai Metro system that loops around central districts and provides key transfer connections across the network.
  • 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 4
Triple: [Paris Metro, hasLine, Line 4]
Generated description
Line 4 is one of the main north–south lines of the Paris Métro, known for serving central Paris and connecting key railway stations and neighborhoods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 4
Target entity description: Line 4 is one of the main north–south lines of the Paris Métro, known for serving central Paris and connecting key railway stations and neighborhoods.
  • A. Line 4
    Line 4 is one of the main lines of the Tehran Metro rapid transit system, serving key east–west corridors across Iran’s capital city.
  • B. Line 4
    Line 4 is a major north–south rapid transit route in the Beijing Subway system, serving key commercial, residential, and university areas of the city.
  • C. Line 4
    Line 4 is a circular rapid transit route of the Shanghai Metro system that loops around central districts and provides key transfer connections across the network.
  • D. Line 4
    Line 4 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving key urban and suburban areas along its north–south corridor.
  • E. Line 4
    Line 4 is a major line of the Santiago Metro in Chile, serving key residential and commercial areas in the southeastern part of 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03e7a7481909c5b902034390ef1 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adead8e9148190b7cba0f325dc58c4 completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adeb6e8fe08190a4732d42aa15ee8e completed March 8, 2026, 9:34 p.m.
NED2 Entity disambiguation (via description) batch_69adebea03a08190bd055e3e6460b5f4 completed March 8, 2026, 9:36 p.m.
Created at: March 4, 2026, 7:33 p.m.