Triple

T3209872
Position Surface form Disambiguated ID Type / Status
Subject Lublin–Brest Offensive E67252 entity
Predicate capturedCity P8411 FINISHED
Object Siedlce E302354 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: Siedlce | Statement: [Lublin–Brest Offensive, capturedCity, Siedlce]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siedlce
Context triple: [Lublin–Brest Offensive, capturedCity, Siedlce]
  • A. Siedlce chosen
    Siedlce is a city in eastern Poland known as a local economic, cultural, and transportation hub.
  • B. Sochaczew
    Sochaczew is a town in central Poland known for its historical significance, particularly during World War II, and its location along the Bzura River west of Warsaw.
  • C. Sieradz
    Sieradz is one of the oldest towns in central Poland, historically significant as a regional center and former royal city.
  • D. Radom
    Radom is a city in central Poland known as an important regional industrial and cultural center.
  • E. Ciechanów
    Ciechanów is a historic town in east-central Poland, known as a regional center of the Mazovian area with a medieval castle and long-standing cultural traditions.
  • 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_69ad858ac36c81909962589cd277d6e2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaab701c48190b91404ab416f7ce3 completed March 8, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf779f7d54819083e1cb88e34c6d34 completed March 22, 2026, 5:01 a.m.
Created at: March 8, 2026, 3:07 p.m.