Triple

T1658605
Position Surface form Disambiguated ID Type / Status
Subject Tehran Metro E35854 entity
Predicate hasLine P35 FINISHED
Object Line 3
Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
 E192417 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 3 | Statement: [Tehran Metro, hasLine, Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 3
Context triple: [Tehran Metro, hasLine, Line 3]
  • A. Line 3
    Line 3 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 3
    Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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 3
Triple: [Tehran Metro, hasLine, Line 3]
Generated description
Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 3
Target entity description: Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
  • A. Line 3
    Line 3 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 3
    Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69a88606aa808190aa0b421b4271f220 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90aafe5e881908158fab83998fd07 completed March 5, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8abe91bc8190ba363e1f7fd07b9f completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad9575acf88190aa3fe80794534dd4 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97a7128c819097ff36216f00d4f9 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:29 p.m.