Triple

T17273910
Position Surface form Disambiguated ID Type / Status
Subject Můstek station E419335 entity
Predicate hasTransferTo P17241 FINISHED
Object Line B
Line B is one of the main lines of the Prague Metro system, running in an east–west direction across the city.
 E393164 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 B | Statement: [Můstek station, hasTransferTo, Line B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line B
Context triple: [Můstek station, hasTransferTo, Line B]
  • A. Line B
    Line B is one of the main rapid transit lines of the Medellín Metro system, serving several neighborhoods in the Aburrá Valley metropolitan area.
  • B. Line B
    Line B is one of the main routes of the Porto Metro light rail system in Porto, Portugal, connecting key suburban areas with the city center.
  • C. Line B
    Line B is one of the main routes of the Rotterdam Metro rapid transit system, serving multiple districts and suburbs in and around Rotterdam.
  • D. Line B
    Line B is one of the main lines of the Buenos Aires Underground, running through key commercial and residential areas of the city.
  • E. Line B
    Line B is one of the main routes of the Strasbourg tramway network, serving key districts and connecting important transit hubs 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 B
Triple: [Můstek station, hasTransferTo, Line B]
Generated description
Line B is one of the main lines of the Prague Metro system, running in an east–west direction across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line B
Target entity description: Line B is one of the main lines of the Prague Metro system, running in an east–west direction across the city.
  • A. Line B chosen
    Line B is one of the main lines of the Prague Metro system, running east–west across the city and serving numerous central and residential districts.
  • B. Line B
    Line B is one of the main lines of the Buenos Aires Underground, running through key commercial and residential areas of the city.
  • C. Line B
    Line B is one of the main routes of the Rotterdam Metro rapid transit system, serving multiple districts and suburbs in and around Rotterdam.
  • D. Line B
    Line B is a major Mexico City Metro route that runs diagonally across the city, connecting central areas with northeastern suburbs and serving as an important commuter corridor.
  • E. Line B
    Line B is one of the main routes of the Strasbourg tramway network, serving key districts and connecting important transit hubs across the city.
  • F. None of above.

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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42f4c209c81909c713ed78f2cb19a completed April 19, 2026, 1:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180d08c9c8190ae139cd92720028a completed May 11, 2026, 7:10 a.m.
NEDg Description generation batch_6a0183f6baf88190b37586af9d1ea7df completed May 11, 2026, 7:23 a.m.
NED2 Entity disambiguation (via description) batch_6a01844ac8808190b2f974d498d3a938 completed May 11, 2026, 7:24 a.m.
Created at: April 10, 2026, 5:40 a.m.