Triple

T9542856
Position Surface form Disambiguated ID Type / Status
Subject Planernaya E230198 entity
Predicate metroLineNumber P1864 FINISHED
Object Line 7
Line 7 is a line of the Moscow Metro system, known as the Tagansko-Krasnopresnenskaya Line, serving various districts across the city.
E805797 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: [Planernaya, metroLineNumber, Line 7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 7
Context triple: [Planernaya, metroLineNumber, 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 a Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
  • D. Line 7
    Line 7 is a rapid transit route of the STC Metro system, serving as one of its numbered lines within the network.
  • E. Line 7
    Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
  • 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: [Planernaya, metroLineNumber, Line 7]
Generated description
Line 7 is a line of the Moscow Metro system, known as the Tagansko-Krasnopresnenskaya Line, serving various districts across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 7
Target entity description: Line 7 is a line of the Moscow Metro system, known as the Tagansko-Krasnopresnenskaya Line, serving various districts across the city.
  • A. Line 7
    Line 7 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts across the city.
  • B. Line 7
    Line 7 is the Pink Line of the Delhi Metro, a major orbital corridor that connects numerous key residential and commercial areas across Delhi.
  • C. 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.
  • D. Line 7
    Line 7 is an east–west rapid transit line of the Beijing Subway serving several central and southwestern districts of Beijing.
  • 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_69ca847c70b8819088a0a0bad64a50d6 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e9be048190bf1f01884ff7c362 completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c6538b08190a9f81304214a876d completed April 4, 2026, 5:37 p.m.
NEDg Description generation batch_69d14d44b7f08190b66fecb315b37535 completed April 4, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_69d14e0823e881908ed723d20f14789b completed April 4, 2026, 5:44 p.m.
Created at: March 30, 2026, 8:01 p.m.