Triple

T3817697
Position Surface form Disambiguated ID Type / Status
Subject Prague Metro E84295 entity
Predicate hasStation P35 FINISHED
Object Háje
Háje is a Prague Metro station serving as the southern terminus of Line C in the Háje district of the city.
 E390331 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: Háje | Statement: [Prague Metro, hasStation, Háje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Háje
Context triple: [Prague Metro, hasStation, Háje]
  • A. Havelterberg
    Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
  • B. Haná
    Haná is a historical ethnographic region in central Moravia in the Czech Republic, known for its fertile agricultural land, distinctive folk traditions, and Hanakian dialect.
  • C. Kaliště
    Kaliště is a small village in the Czech Republic best known as the birthplace of composer Gustav Mahler.
  • D. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • E. Hlohov
    Hlohov is the Czech name for the Polish city of Głogów, a historic town in Lower Silesia known for its medieval heritage and strategic location on the Oder River.
  • 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: Háje
Triple: [Prague Metro, hasStation, Háje]
Generated description
Háje is a Prague Metro station serving as the southern terminus of Line C in the Háje district of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Háje
Target entity description: Háje is a Prague Metro station serving as the southern terminus of Line C in the Háje district of the city.
  • A. Havelterberg
    Havelterberg is a modest hill and natural area in the Dutch province of Drenthe, known for its scenic landscapes and prehistoric burial mounds.
  • B. Haná
    Haná is a historical ethnographic region in central Moravia in the Czech Republic, known for its fertile agricultural land, distinctive folk traditions, and Hanakian dialect.
  • C. Kaliště
    Kaliště is a small village in the Czech Republic best known as the birthplace of composer Gustav Mahler.
  • D. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • E. Hlohov
    Hlohov is the Czech name for the Polish city of Głogów, a historic town in Lower Silesia known for its medieval heritage and strategic location on the Oder River.
  • 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_69aed931f5908190be2c07af66d4df25 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeea5e41ec81908ed7e1ccc2713622 completed March 9, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb43e1d481909a5b52cae5686179 completed March 14, 2026, 6:08 a.m.
NEDg Description generation batch_69b4fcec1cf48190aa0b128acb56c089 completed March 14, 2026, 6:15 a.m.
NED2 Entity disambiguation (via description) batch_69b4fd4d55248190bf4ef442a9991edf completed March 14, 2026, 6:16 a.m.
Created at: March 9, 2026, 3:17 p.m.