Triple

T17442580
Position Surface form Disambiguated ID Type / Status
Subject Písek E424693 entity
Predicate touristAttraction P530 FINISHED
Object old town — NE NERFINISHED

How this triple was built (3 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: old town | Statement: [Písek, touristAttraction, old town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: old town
Context triple: [Písek, touristAttraction, old town]
  • A. old town
    The old town of Chalon-sur-Saône is a historic district characterized by medieval streets, traditional Burgundy architecture, and notable heritage buildings reflecting the city’s past as an important river port.
  • B. City of Old Town
    The City of Old Town is a municipal government that administers local services, governance, and public safety for the community of Old Town.
  • C. historic Old Town
    The historic Old Town of Lublin is a well-preserved medieval district known for its narrow cobbled streets, Renaissance and Gothic architecture, and significant role in Polish cultural and political history.
  • D. historic Old Town
    The historic Old Town of Przemyśl is a well-preserved medieval city center in southeastern Poland, known for its picturesque architecture, cobbled streets, and layered multicultural history.
  • E. Old Town (historic city center)
    Old Town (historic city center) is the medieval core of Székesfehérvár, characterized by its historic architecture, narrow streets, and significant cultural and religious monuments.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: old town
Target entity description: The old town of Písek is a historic district known for its preserved medieval architecture, charming streets, and cultural landmarks along the Otava River in the Czech Republic.
  • A. old town
    The old town of Chalon-sur-Saône is a historic district characterized by medieval streets, traditional Burgundy architecture, and notable heritage buildings reflecting the city’s past as an important river port.
  • B. City of Old Town
    The City of Old Town is a municipal government that administers local services, governance, and public safety for the community of Old Town.
  • C. historic Old Town
    The historic Old Town of Lublin is a well-preserved medieval district known for its narrow cobbled streets, Renaissance and Gothic architecture, and significant role in Polish cultural and political history.
  • D. historic Old Town
    The historic Old Town of Przemyśl is a well-preserved medieval city center in southeastern Poland, known for its picturesque architecture, cobbled streets, and layered multicultural history.
  • E. Old Town (historic city center)
    Old Town (historic city center) is the medieval core of Székesfehérvár, characterized by its historic architecture, narrow streets, and significant cultural and religious monuments.
  • F. None of above. chosen

Provenance (2 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44ff82bbc819095dd0621137da809 completed April 19, 2026, 3:46 a.m.
Created at: April 10, 2026, 5:47 a.m.