Triple

T11870688
Position Surface form Disambiguated ID Type / Status
Subject Metro Line 9 E282398 entity
Predicate connectsWithLine P845 FINISHED
Object Line 3
Line 3 is a metro line that intersects with Metro Line 9 within the same urban rail network, serving as one of its connecting routes.
E953244 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: [Metro Line 9, connectsWithLine, Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 3
Context triple: [Metro Line 9, connectsWithLine, Line 3]
  • A. 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.
  • B. Line 3
    Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
  • C. Line 3
    Line 3 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key urban districts along a major north–south corridor.
  • D. Line 3
    Line 3 is a future rapid transit route of the Seville Metro intended to extend and improve the city’s urban rail network.
  • E. Line 3
    Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
  • 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: [Metro Line 9, connectsWithLine, Line 3]
Generated description
Line 3 is a metro line that intersects with Metro Line 9 within the same urban rail network, serving as one of its connecting routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 3
Target entity description: Line 3 is a metro line that intersects with Metro Line 9 within the same urban rail network, serving as one of its connecting routes.
  • A. Line 3
    Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
  • B. Line 3
    Line 3 is a major rapid transit route of the STC Metro system, serving key districts along its corridor.
  • C. Line 3
    Line 3 is a major north–south route of the Seoul Metropolitan Subway system, connecting key residential and commercial districts across the city and into surrounding areas.
  • D. Line 3
    Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
  • E. Line 3
    Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be15fb2481908f514781ce2c617f completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f417bb131c8190b0923e077cca74be completed May 1, 2026, 3:02 a.m.
NEDg Description generation batch_69f41f8d297c81908cfe60b10989e550 completed May 1, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69f422778a10819093bc2473ef30fe71 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:43 p.m.