Triple

T23583738
Position Surface form Disambiguated ID Type / Status
Subject Holocaust in Belarus E582277 entity
Predicate tookPlaceIn P40 FINISHED
Object Baranovichi Ghetto
The Baranovichi Ghetto was a Nazi-established Jewish ghetto in occupied Belarus where thousands of Jews were confined, exploited, and ultimately murdered during the Holocaust.
E1632918 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: Baranovichi Ghetto | Statement: [Holocaust in Belarus, tookPlaceIn, Baranovichi Ghetto]
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: Baranovichi Ghetto
Triple: [Holocaust in Belarus, tookPlaceIn, Baranovichi Ghetto]
Generated description
The Baranovichi Ghetto was a Nazi-established Jewish ghetto in occupied Belarus where thousands of Jews were confined, exploited, and ultimately murdered during the Holocaust.

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_69e248f8d8248190acd5aee77f0d1709 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b02e19808190a41bce305f6cd5da completed April 29, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd628271481908d93249f85e3aa11 completed May 22, 2026, 4:06 a.m.
NEDg Description generation batch_6a0fd73ea7d88190b9bd774def308d97 completed May 22, 2026, 4:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0fdb3919fc8190a66f585aff4e7570 completed May 22, 2026, 4:27 a.m.
Created at: April 17, 2026, 6:40 p.m.