Triple

T8597459
Position Surface form Disambiguated ID Type / Status
Subject Frýdek E203586 entity
Predicate mergedWith P77 FINISHED
Object Místek
Místek is a town in the Czech Republic that now forms part of the city of Frýdek-Místek following their administrative merger.
 E746324 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: Místek | Statement: [Frýdek, mergedWith, Místek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Místek
Context triple: [Frýdek, mergedWith, Místek]
  • A. Mukalla
    Mukalla is a major port city on Yemen’s southern coast and the capital of the Hadhramaut Governorate.
  • B. Tivissa
    Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
  • C. Ostredok
    Ostredok is the highest peak of the Veľká Fatra range in central Slovakia, known for its rounded grassy summit and panoramic views.
  • D. Munirka
    Munirka is a densely populated residential and commercial neighborhood in South Delhi, known for its urban village character, proximity to major institutions, and extensive rental housing.
  • E. Ocuvite
    Ocuvite is a line of eye health dietary supplements formulated to support and protect vision, particularly in aging adults.
  • 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: Místek
Triple: [Frýdek, mergedWith, Místek]
Generated description
Místek is a town in the Czech Republic that now forms part of the city of Frýdek-Místek following their administrative merger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Místek
Target entity description: Místek is a town in the Czech Republic that now forms part of the city of Frýdek-Místek following their administrative merger.
  • A. Mukalla
    Mukalla is a major port city on Yemen’s southern coast and the capital of the Hadhramaut Governorate.
  • B. Tivissa
    Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
  • C. Ostredok
    Ostredok is the highest peak of the Veľká Fatra range in central Slovakia, known for its rounded grassy summit and panoramic views.
  • D. Munirka
    Munirka is a densely populated residential and commercial neighborhood in South Delhi, known for its urban village character, proximity to major institutions, and extensive rental housing.
  • E. Ocuvite
    Ocuvite is a line of eye health dietary supplements formulated to support and protect vision, particularly in aging adults.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46cacbe88190b95beeedc9f480b0 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8d3fcfc8190bc51a38715ed453e completed April 2, 2026, 5:35 p.m.
NEDg Description generation batch_69ceac90764c81908c349729bd22a9af completed April 2, 2026, 5:51 p.m.
NED2 Entity disambiguation (via description) batch_69cead4a4f148190aa39e774528730c9 completed April 2, 2026, 5:54 p.m.
Created at: March 30, 2026, 6:24 p.m.