Triple

T14968672
Position Surface form Disambiguated ID Type / Status
Subject Działdowo E373258 entity
Predicate nearbyCity P350 FINISHED
Object Mława NE NERFINISHED

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: Mława | Statement: [Działdowo, nearbyCity, Mława]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mława
Context triple: [Działdowo, nearbyCity, Mława]
  • A. Mława chosen
    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.
  • B. Muszyna
    Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
  • C. Głuszyna
    Głuszyna is a locality in present-day Poland known as the birthplace of the 19th-century Polish explorer and geologist Paweł Edmund Strzelecki.
  • D. Skawica
    Skawica is a village in southern Poland, located in the Lesser Poland Voivodeship within the administrative district of powiat suski.
  • E. Byczyna
    Byczyna is a historic small town in southwestern Poland known for its well-preserved medieval urban layout and defensive walls.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6e44cb0819096e09f8026ef8174 completed April 15, 2026, 12:08 a.m.
Created at: April 10, 2026, 2:48 a.m.