Triple

T1658603
Position Surface form Disambiguated ID Type / Status
Subject Tehran Metro E35854 entity
Predicate hasLine P35 FINISHED
Object Line 1
Line 1 is the main north–south route of the Tehran Metro system, serving as one of its busiest and most important rapid transit lines.
 E187608 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 1 | Statement: [Tehran Metro, hasLine, Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 1
Context triple: [Tehran Metro, hasLine, Line 1]
  • A. Line 1
    Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
  • B. Line 1
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • C. Line 1
    Line 1 is the oldest and one of the busiest lines of the Mexico City Metro, running east–west across the city and serving many central, high-traffic stations.
  • D. Line 1
    Line 1 is a major rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's primary east–west corridors.
  • E. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west 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 1
Triple: [Tehran Metro, hasLine, Line 1]
Generated description
Line 1 is the main north–south route of the Tehran Metro system, serving as one of its busiest and most important rapid transit lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 1
Target entity description: Line 1 is the main north–south route of the Tehran Metro system, serving as one of its busiest and most important rapid transit lines.
  • A. Line 1
    Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
  • B. Line 1
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • C. Line 1
    Line 1 is the oldest and one of the busiest lines of the Mexico City Metro, running east–west across the city and serving many central, high-traffic stations.
  • D. Line 1
    Line 1 is a major rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's primary east–west corridors.
  • E. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west 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_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_69ad6827ff2c8190b7c9af9926a7452c completed March 8, 2026, 12:14 p.m.
NEDg Description generation batch_69ad68edbd2c819090c6556966eb279a completed March 8, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_69ad69724c9c8190a2314a8f30f18f7d completed March 8, 2026, 12:20 p.m.
Created at: March 4, 2026, 7:29 p.m.