Triple

T7114686
Position Surface form Disambiguated ID Type / Status
Subject Sofia Metro E165788 entity
Predicate hasStation P35 FINISHED
Object Obelya station
Obelya station is a metro station in Sofia, Bulgaria, serving as an interchange point between lines of the Sofia Metro network.
 E647559 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: Obelya station | Statement: [Sofia Metro, hasStation, Obelya station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Obelya station
Context triple: [Sofia Metro, hasStation, Obelya station]
  • A. Frunzenskaya station
    Frunzenskaya station is a Moscow Metro station known for its deep-level construction and classic Soviet-era architectural design.
  • B. Timiryazevskaya station
    Timiryazevskaya station is a Moscow Metro station that serves as a key stop and namesake on the Serpukhovsko–Timiryazevskaya Line.
  • C. Krasnoselskaya station
    Krasnoselskaya station is a Moscow Metro station known for its early Soviet-era architecture and location on the system’s first metro line.
  • D. Troparyovo station
    Troparyovo station is a Moscow Metro station serving the southwestern part of the city on one of its main radial lines.
  • E. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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: Obelya station
Triple: [Sofia Metro, hasStation, Obelya station]
Generated description
Obelya station is a metro station in Sofia, Bulgaria, serving as an interchange point between lines of the Sofia Metro network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Obelya station
Target entity description: Obelya station is a metro station in Sofia, Bulgaria, serving as an interchange point between lines of the Sofia Metro network.
  • A. Frunzenskaya station
    Frunzenskaya station is a Moscow Metro station known for its deep-level construction and classic Soviet-era architectural design.
  • B. Timiryazevskaya station
    Timiryazevskaya station is a Moscow Metro station that serves as a key stop and namesake on the Serpukhovsko–Timiryazevskaya Line.
  • C. Krasnoselskaya station
    Krasnoselskaya station is a Moscow Metro station known for its early Soviet-era architecture and location on the system’s first metro line.
  • D. Troparyovo station
    Troparyovo station is a Moscow Metro station serving the southwestern part of the city on one of its main radial lines.
  • E. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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_69c6888227bc8190a1394679e3116f90 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e5f0dab8819092103aefcaa1f9c2 completed March 27, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8d92fec8190bd275023bdef8e08 completed March 28, 2026, 11:17 a.m.
NEDg Description generation batch_69c7b9c1afe48190bc55468790e84067 completed March 28, 2026, 11:21 a.m.
NED2 Entity disambiguation (via description) batch_69c7ba441f8c8190a4f88b140a1563f9 completed March 28, 2026, 11:23 a.m.
Created at: March 27, 2026, 2:43 p.m.