Triple

T2418995
Position Surface form Disambiguated ID Type / Status
Subject Edward Gierek E52373 entity
Predicate workLocation P7 FINISHED
Object Katowice E32146 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: Katowice | Statement: [Edward Gierek, workLocation, Katowice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katowice
Context triple: [Edward Gierek, workLocation, Katowice]
  • A. Katowice chosen
    Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
  • B. Wrocław
    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.
  • C. Gliwice
    Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
  • D. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • E. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc96e1b3881909de57501b5d4099a completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69b528071e488190ac531404dac9587c completed March 14, 2026, 9:19 a.m.
Created at: March 6, 2026, 9:42 p.m.