Triple

T4751062
Position Surface form Disambiguated ID Type / Status
Subject Stockholm commuter rail E105476 entity
Predicate hasLine P35 FINISHED
Object line J35
Line J35 is a route within the Stockholm commuter rail network that serves suburban and regional passengers traveling to and from the Swedish capital.
 E467341 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 J35 | Statement: [Stockholm commuter rail, hasLine, line J35]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: line J35
Context triple: [Stockholm commuter rail, hasLine, line J35]
  • A. line J
    Line J is a suburban rail line in the Transilien network serving the western suburbs of Paris, particularly along the Paris–Saint-Lazare corridor.
  • B. Line 3
    Line 3 is a major trolleybus route within Geneva’s public transport system, connecting key districts of the city.
  • C. Line 3
    Line 3 is a major Athens Metro route that connects central Athens with key destinations including the Athens International Airport.
  • D. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • 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
  • 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 J35
Triple: [Stockholm commuter rail, hasLine, line J35]
Generated description
Line J35 is a route within the Stockholm commuter rail network that serves suburban and regional passengers traveling to and from the Swedish capital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: line J35
Target entity description: Line J35 is a route within the Stockholm commuter rail network that serves suburban and regional passengers traveling to and from the Swedish capital.
  • A. line J
    Line J is a suburban rail line in the Transilien network serving the western suburbs of Paris, particularly along the Paris–Saint-Lazare corridor.
  • B. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • C. 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.
  • D. Line 3
    Line 3 is a major trolleybus route within Geneva’s public transport system, connecting key districts of the city.
  • E. Line 3
    Line 3 is a major Athens Metro route that connects central Athens with key destinations including the Athens International Airport.
  • 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_69bd43f07fa48190954317d01600994a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64c97b548190815083f2f8df907c completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a561a7c8190a5ab87751ab36e0d completed March 21, 2026, 6:27 a.m.
NEDg Description generation batch_69be3d2063e48190afb3fdfd5ad6749f completed March 21, 2026, 6:39 a.m.
NED2 Entity disambiguation (via description) batch_69be3d99a288819088e42e04de5c17a4 completed March 21, 2026, 6:41 a.m.
Created at: March 20, 2026, 1:20 p.m.