Triple

T31527746
Position Surface form Disambiguated ID Type / Status
Subject Independence Avenue (Minsk) E804390 entity
Predicate hasSiteOnStreet P959 FINISHED
Object October Square (Minsk)
October Square (Minsk) is a central public square in the heart of Minsk, Belarus, known for its prominent government buildings, cultural venues, and role as a major civic and ceremonial space.
E1972654 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: October Square (Minsk) | Statement: [Independence Avenue (Minsk), hasSiteOnStreet, October Square (Minsk)]
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: October Square (Minsk)
Triple: [Independence Avenue (Minsk), hasSiteOnStreet, October Square (Minsk)]
Generated description
October Square (Minsk) is a central public square in the heart of Minsk, Belarus, known for its prominent government buildings, cultural venues, and role as a major civic and ceremonial space.

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_69f348cf839c81908657048402f7f97b completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69fce5b76ca08190b7afe94963997184 completed May 7, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b849e9d608190b27f0460e46c0a45 completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b85377adc8190b4c886d2a585a84b completed June 12, 2026, 4:04 a.m.
NED2 Entity disambiguation (via description) batch_6a2b8598ebb481909235beb350564bce completed June 12, 2026, 4:05 a.m.
Created at: April 30, 2026, 9:59 p.m.