Triple

T8581494
Position Surface form Disambiguated ID Type / Status
Subject Civitanova Marche E203189 entity
Predicate twinTown P1072 FINISHED
Object Skawina E23073 NE FINISHED

How this triple was built (2 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: Skawina | Statement: [Civitanova Marche, twinTown, Skawina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skawina
Context triple: [Civitanova Marche, twinTown, Skawina]
  • A. Skawina chosen
    Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
  • B. Wiślica
    Wiślica is a historic town in south-central Poland, known for its medieval architecture and archaeological significance as one of the country’s oldest settlements.
  • C. Mława
    Mława is a town in north-central Poland known for its historical significance, including a major World War II battle, and its regional cultural and economic role.
  • D. Słupia
    Słupia is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • E. Muszyna
    Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8329bb7c8190a63c643730839103 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbeb1bbbd8819082670286a711826d completed March 31, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89ae87f08190b83bc539e1d4eeaa completed April 2, 2026, 3:22 p.m.
Created at: March 30, 2026, 6:22 p.m.