Triple

T19181723
Position Surface form Disambiguated ID Type / Status
Subject Janów Lubelski E469589 entity
Predicate nearbyCity P350 FINISHED
Object Lublin 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: Lublin | Statement: [Janów Lubelski, nearbyCity, Lublin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lublin
Context triple: [Janów Lubelski, nearbyCity, Lublin]
  • A. Lublin chosen
    Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
  • B. Łódź
    Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
  • C. Radom
    Radom is a city in central Poland known as an important regional industrial and cultural center.
  • D. Kielce
    Kielce is a city in south-central Poland known as an important regional center for industry, education, and culture.
  • E. Olsztyn
    Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of the Warmian-Masurian Voivodeship.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f61cab348190965e96ac0f701f9f completed April 20, 2026, 9:47 a.m.
Created at: April 10, 2026, 12:07 p.m.