Triple

T1658607
Position Surface form Disambiguated ID Type / Status
Subject Tehran Metro E35854 entity
Predicate hasLine P35 FINISHED
Object Line 5
Line 5 is a commuter rail line of the Tehran Metro system that connects central Tehran with its western suburbs and satellite cities.
 E199302 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 5 | Statement: [Tehran Metro, hasLine, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 5
Context triple: [Tehran Metro, hasLine, Line 5]
  • A. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • B. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • C. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • D. Line 5
    Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
  • E. Line 5
    Line 5 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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 5
Triple: [Tehran Metro, hasLine, Line 5]
Generated description
Line 5 is a commuter rail line of the Tehran Metro system that connects central Tehran with its western suburbs and satellite cities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 5
Target entity description: Line 5 is a commuter rail line of the Tehran Metro system that connects central Tehran with its western suburbs and satellite cities.
  • A. Line 5
    Line 5 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 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • C. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • D. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • E. Line 5
    Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
  • 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_69ada972c92c8190b5c69cd9223ad0f6 completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adae972d1081909cd13e8220c3ccc6 completed March 8, 2026, 5:15 p.m.
NED2 Entity disambiguation (via description) batch_69adaf9d042481909dbd54d9e04e444e completed March 8, 2026, 5:19 p.m.
Created at: March 4, 2026, 7:29 p.m.