Triple

T17162898
Position Surface form Disambiguated ID Type / Status
Subject Bielany E416525 entity
Predicate hasMetroStation P522 FINISHED
Object Młociny
Młociny is a northern Warsaw neighborhood best known as the terminus of the city’s M1 metro line and a major transport hub.
 E1490028 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: Młociny | Statement: [Bielany, hasMetroStation, Młociny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Młociny
Context triple: [Bielany, hasMetroStation, Młociny]
  • A. Mikołów
    Mikołów is a historic town in southern Poland known for its traditional Silesian character and proximity to the regional capital, Katowice.
  • B. Miechów
    Miechów is a historic town in southern Poland known for its medieval heritage and religious significance, particularly the Basilica of the Holy Sepulchre.
  • C. Mszana Dolna
    Mszana Dolna is a small town in southern Poland situated in a picturesque valley surrounded by the mountains of the Western Beskids.
  • D. Pszczyna
    Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
  • E. Bochorna
    Bochorna is a remote highland village in the Tusheti region of northeastern Georgia, known as one of the highest permanently inhabited settlements in Europe.
  • 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: Młociny
Triple: [Bielany, hasMetroStation, Młociny]
Generated description
Młociny is a northern Warsaw neighborhood best known as the terminus of the city’s M1 metro line and a major transport hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Młociny
Target entity description: Młociny is a northern Warsaw neighborhood best known as the terminus of the city’s M1 metro line and a major transport hub.
  • A. Mikołów
    Mikołów is a historic town in southern Poland known for its traditional Silesian character and proximity to the regional capital, Katowice.
  • B. Miechów
    Miechów is a historic town in southern Poland known for its medieval heritage and religious significance, particularly the Basilica of the Holy Sepulchre.
  • C. Mszana Dolna
    Mszana Dolna is a small town in southern Poland situated in a picturesque valley surrounded by the mountains of the Western Beskids.
  • D. Pszczyna
    Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
  • E. Bochorna
    Bochorna is a remote highland village in the Tusheti region of northeastern Georgia, known as one of the highest permanently inhabited settlements in Europe.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f91316108190b0d856d6fa5cd509 completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09eec4ce9c8190b76efb4d6f038125 completed May 17, 2026, 4:37 p.m.
NEDg Description generation batch_6a09efc6a57c81908c72e794c16989d4 completed May 17, 2026, 4:41 p.m.
NED2 Entity disambiguation (via description) batch_6a09f07a090c8190aead09c3b06e0e34 completed May 17, 2026, 4:44 p.m.
Created at: April 10, 2026, 5:37 a.m.