Triple

T35927614
Position Surface form Disambiguated ID Type / Status
Subject downtown Poznań E1039068 entity
Predicate hasLandmark P105 FINISHED
Object Garbary Street in Poznań
Garbary Street in Poznań is a major historic thoroughfare running along the eastern edge of the Old Town, known for its mix of tenement architecture, commercial activity, and role as a key inner-city traffic route.
E2169285 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: Garbary Street in Poznań | Statement: [downtown Poznań, hasLandmark, Garbary Street in Poznań]
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: Garbary Street in Poznań
Triple: [downtown Poznań, hasLandmark, Garbary Street in Poznań]
Generated description
Garbary Street in Poznań is a major historic thoroughfare running along the eastern edge of the Old Town, known for its mix of tenement architecture, commercial activity, and role as a key inner-city traffic route.

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_69f76e23e4688190a5369138755138bf completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ab7e11b481908949cdea947bfe1f completed May 3, 2026, 8:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ddef3c2c819080d40e9e0958e42a completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38de873810819084ae1ee5c52be65a completed June 22, 2026, 7:04 a.m.
NED2 Entity disambiguation (via description) batch_6a38df04c6e881908a0ad5b6abcfe7be completed June 22, 2026, 7:06 a.m.
Created at: May 3, 2026, 4:07 p.m.