Triple

T2639990
Position Surface form Disambiguated ID Type / Status
Subject Berl Katznelson E62841 entity
Predicate placeOfBirth P1 FINISHED
Object Babruysk
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
 E295542 NE FINISHED

How this triple was built (4 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: Babruysk | Statement: [Berl Katznelson, placeOfBirth, Babruysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Babruysk
Context triple: [Berl Katznelson, placeOfBirth, Babruysk]
  • A. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • B. Novopolotsk
    Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
  • C. Elbing
    Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • D. Mogilev
    Mogilev is a major city in eastern Belarus known as an important industrial and cultural center on the Dnieper River.
  • E. Brest (Belarus)
    Brest is a city in southwestern Belarus near the Polish border, known as a major transport hub and for the historic Brest Fortress, a key World War II memorial.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Babruysk
Triple: [Berl Katznelson, placeOfBirth, Babruysk]
Generated description
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Babruysk
Target entity description: Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
  • A. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • B. Novopolotsk
    Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
  • C. Elbing
    Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • D. Mogilev
    Mogilev is a major city in eastern Belarus known as an important industrial and cultural center on the Dnieper River.
  • E. Brest (Belarus)
    Brest is a city in southwestern Belarus near the Polish border, known as a major transport hub and for the historic Brest Fortress, a key World War II memorial.
  • F. None of above. chosen

Provenance (5 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8fafad08190939b08558fea6abd completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbb328a88190b0ef889cbbe3bea3 completed March 10, 2026, 6:35 a.m.
NEDg Description generation batch_69afbce109f48190be1a31d9300dbee6 completed March 10, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69afbda490ac8190bb12598e26b91677 completed March 10, 2026, 6:43 a.m.
Created at: March 6, 2026, 9:53 p.m.