Triple

T892518
Position Surface form Disambiguated ID Type / Status
Subject Paul von Hindenburg E19271 entity
Predicate birthPlace P1 FINISHED
Object Posen E14540 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: Posen | Statement: [Paul von Hindenburg, birthPlace, Posen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Posen
Context triple: [Paul von Hindenburg, birthPlace, Posen]
  • A. Poznań chosen
    Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
  • B. 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.
  • C. Lublin
    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.
  • D. Gdańsk
    Gdańsk is a major Polish port city on the Baltic Sea, known for its rich Hanseatic history, shipyards, and role in the origins of the Solidarity movement.
  • E. Toruń
    Toruń is a historic city in northern Poland, renowned for its well-preserved medieval Old Town and as the birthplace of astronomer Nicolaus Copernicus.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad0304b081908d4c92bb2beadb81 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69acddfa1d48819081538d6505fa062c completed March 8, 2026, 2:24 a.m.
Created at: March 1, 2026, 7:39 p.m.