Triple

T35840248
Position Surface form Disambiguated ID Type / Status
Subject Old Town, Poznań E1036056 entity
Predicate hasPart P35 FINISHED
Object Gołębia Street, Poznań
Gołębia Street in Poznań is a historic lane in the city’s Old Town, known for its traditional townhouses and proximity to key cultural and architectural landmarks.
 E2161951 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: Gołębia Street, Poznań | Statement: [Old Town, Poznań, hasPart, Gołębia Street, 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: Gołębia Street, Poznań
Triple: [Old Town, Poznań, hasPart, Gołębia Street, Poznań]
Generated description
Gołębia Street in Poznań is a historic lane in the city’s Old Town, known for its traditional townhouses and proximity to key cultural and architectural landmarks.

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_69f76e1a29e8819088280f26096aeb55 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a930469081909a00649e471df29f completed May 3, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae19aa888190a646eec4bf79fd60 completed June 22, 2026, 3:38 a.m.
NEDg Description generation batch_6a38aeef45b88190bd73e62d7b0ad345 completed June 22, 2026, 3:41 a.m.
NED2 Entity disambiguation (via description) batch_6a38af81c16c81909e60702d8d3280c3 completed June 22, 2026, 3:44 a.m.
Created at: May 3, 2026, 4:06 p.m.