Triple

T26866064
Position Surface form Disambiguated ID Type / Status
Subject Dzyatlava E676472 entity
Predicate hasHistoricSite P1098 FINISHED
Object Jewish cemetery in Dzyatlava
The Jewish cemetery in Dzyatlava is a historic burial ground preserving the memory of the town’s once-significant Jewish community and its cultural heritage.
 E1744975 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: Jewish cemetery in Dzyatlava | Statement: [Dzyatlava, hasHistoricSite, Jewish cemetery in Dzyatlava]
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: Jewish cemetery in Dzyatlava
Triple: [Dzyatlava, hasHistoricSite, Jewish cemetery in Dzyatlava]
Generated description
The Jewish cemetery in Dzyatlava is a historic burial ground preserving the memory of the town’s once-significant Jewish community and its cultural heritage.

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_69eee9ba94bc8190b44c5d4397d04ecd completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61e9802988190b62996063b17e495 completed May 2, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12135a48188190bd5e09a474154230 completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a1215f7b4188190a5b8ded0b634f0bf completed May 23, 2026, 9:02 p.m.
NED2 Entity disambiguation (via description) batch_6a121699a8448190b7fbf43f6f572ce4 completed May 23, 2026, 9:05 p.m.
Created at: April 27, 2026, 5:28 a.m.