Triple

T18807590
Position Surface form Disambiguated ID Type / Status
Subject SL metro E459919 entity
Predicate hasLine P35 FINISHED
Object Line 13
Line 13 is a route of the SL metro system, serving as one of its numbered rapid transit lines.
 E1346815 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 13 | Statement: [SL metro, hasLine, Line 13]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 13
Context triple: [SL metro, hasLine, Line 13]
  • A. Line 13
    Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
  • B. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • C. Line 13
    Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
  • D. Line 13
    Line 13 is a planned rapid transit line of the Shenzhen Metro system in Shenzhen, China.
  • E. Line 13
    Line 13 is one of the busiest and most congested lines of the Paris Métro, running north–south across the city and serving major hubs such as Saint-Lazare.
  • 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 13
Triple: [SL metro, hasLine, Line 13]
Generated description
Line 13 is a route of the SL metro system, serving as one of its numbered rapid transit lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 13
Target entity description: Line 13 is a route of the SL metro system, serving as one of its numbered rapid transit lines.
  • A. Line 13
    Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
  • B. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • C. Line 13
    Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
  • D. Line 13
    Line 13 is a planned rapid transit line of the Shenzhen Metro system in Shenzhen, China.
  • E. Line 13
    Line 13 is one of the busiest and most congested lines of the Paris Métro, running north–south across the city and serving major hubs such as Saint-Lazare.
  • 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3d8ab9c819097834eac798ce810 completed April 20, 2026, 3:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0575aa63288190867ed95aecb75434 completed May 14, 2026, 7:11 a.m.
NEDg Description generation batch_6a0578e4860c8190ad75eceb9a24613e completed May 14, 2026, 7:25 a.m.
NED2 Entity disambiguation (via description) batch_6a0579373644819092e7208ea5ebf8ce completed May 14, 2026, 7:26 a.m.
Created at: April 10, 2026, 11:53 a.m.