Triple

T626331
Position Surface form Disambiguated ID Type / Status
Subject College Park, Maryland E15826 entity
Predicate hasSisterCity P919 FINISHED
Object Lublin, Poland 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, Poland | Statement: [College Park, Maryland, hasSisterCity, Lublin, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lublin, Poland
Context triple: [College Park, Maryland, hasSisterCity, Lublin, Poland]
  • 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. Lutynia, Poland
    Lutynia, Poland is a village in southwestern Poland best known as the site of the historic 1757 Battle of Leuthen during the Seven Years' War.
  • C. Warsaw
    Warsaw is the capital and largest city of Poland, known for its resilient history, especially its near-total destruction in World War II and subsequent postwar reconstruction.
  • D. Łódź
    Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
  • E. Białystok
    Białystok is a city in northeastern Poland best known as the birthplace of L. L. Zamenhof and the cradle of the international language Esperanto.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e587c448190987943a6aad209d1 completed March 1, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a57b53ea008190be1a797f8d1d6c60 completed March 2, 2026, 11:58 a.m.
Created at: March 1, 2026, 7:35 p.m.