Triple

T10193504
Position Surface form Disambiguated ID Type / Status
Subject Breslau E238097 entity
Predicate post1945OfficialNameOfCity P76346 FINISHED
Object Wrocław E17157 NE FINISHED

How this triple was built (3 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: Wrocław | Statement: [Breslau, post1945OfficialNameOfCity, Wrocław]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wrocław
Context triple: [Breslau, post1945OfficialNameOfCity, Wrocław]
  • A. Wrocław chosen
    Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
  • B. Katowice
    Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
  • C. Poznań
    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.
  • D. Kraków
    Kraków is one of Poland’s oldest and most historically significant cities, renowned for its well-preserved medieval core, royal heritage, and cultural institutions.
  • E. Wolsztyn
    Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: post1945OfficialNameOfCity
Context triple: [Breslau, post1945OfficialNameOfCity, Wrocław]
  • A. post1945NameChange chosen
    Indicates that an entity changed its name at some point after the year 1945.
  • B. countryAfterCityRename
    Indicates the country to which a city belongs after the city has undergone a renaming.
  • C. post1945Event
    Indicates that an event occurred after the year 1945.
  • D. locationAfter1949
    Indicates that the specified location is relevant, valid, or applicable only for the time period after the year 1949.
  • E. statusIn1945
    Indicates the condition, role, or classification an entity had specifically during the year 1945.
  • F. None of above.

Provenance (4 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdedc675008190b8248325f5a208bf completed April 2, 2026, 4:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69f671788ec88190852df74698bc4518 completed May 2, 2026, 9:49 p.m.
PD Predicate disambiguation batch_69cd7c8477648190bc55c56aeec507d3 completed April 1, 2026, 8:13 p.m.
Created at: March 30, 2026, 9:13 p.m.