Triple

T26938457
Position Surface form Disambiguated ID Type / Status
Subject Miklošičeva Street E678447 entity
Predicate hasNotableBuilding P1544 FINISHED
Object Grand Hotel Union
Grand Hotel Union is a historic and elegant Art Nouveau hotel in the center of Ljubljana, Slovenia, renowned for its grand architecture and long-standing role in the city’s cultural and social life.
E1746543 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: Grand Hotel Union | Statement: [Miklošičeva Street, hasNotableBuilding, Grand Hotel Union]
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: Grand Hotel Union
Triple: [Miklošičeva Street, hasNotableBuilding, Grand Hotel Union]
Generated description
Grand Hotel Union is a historic and elegant Art Nouveau hotel in the center of Ljubljana, Slovenia, renowned for its grand architecture and long-standing role in the city’s cultural and social life.

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_69eeeb4d69588190a7c912164a1c37b3 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f62050af2481909ce5687b36c4aabc completed May 2, 2026, 4:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121ec47efc81909b1a297f00e68daa completed May 23, 2026, 9:40 p.m.
NEDg Description generation batch_6a121f5c372481909cfd4c5ebc39f5ea completed May 23, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a122004aadc819084dbaa834408a0bc completed May 23, 2026, 9:45 p.m.
Created at: April 27, 2026, 6:17 a.m.