Triple

T27036393
Position Surface form Disambiguated ID Type / Status
Subject Cankarjeva cesta E681064 entity
Predicate connectsWith P37 FINISHED
Object Prešeren Street, Ljubljana
Prešeren Street in Ljubljana is a central pedestrian thoroughfare near Prešeren Square, known for its shops, cafes, and proximity to key cultural and historical landmarks in Slovenia’s capital.
 E1775927 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: Prešeren Street, Ljubljana | Statement: [Cankarjeva cesta, connectsWith, Prešeren Street, Ljubljana]
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: Prešeren Street, Ljubljana
Triple: [Cankarjeva cesta, connectsWith, Prešeren Street, Ljubljana]
Generated description
Prešeren Street in Ljubljana is a central pedestrian thoroughfare near Prešeren Square, known for its shops, cafes, and proximity to key cultural and historical landmarks in Slovenia’s capital.

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_69eeeb5566f08190813daf896fa3da04 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f62267964881909211b55aa013b899 completed May 2, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbbb7bc48190bcff3de0335ffccd completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bd4dacfc81908c61517b7286c35d completed May 24, 2026, 8:56 a.m.
NED2 Entity disambiguation (via description) batch_6a12bdeacda08190bfe8354ed2666d23 completed May 24, 2026, 8:59 a.m.
Created at: April 27, 2026, 7:16 a.m.