Triple

T12656452
Position Surface form Disambiguated ID Type / Status
Subject Lubartów E302295 entity
Predicate hasRailwayConnectionTo P3791 FINISHED
Object Lublin E47827 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: Lublin | Statement: [Lubartów, hasRailwayConnectionTo, Lublin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lublin
Context triple: [Lubartów, hasRailwayConnectionTo, 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 (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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961620b188190a8a8569f1133a9cf completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfcbbf408190a87f471d2732148b completed May 9, 2026, 5:02 a.m.
Created at: April 9, 2026, 5:18 p.m.