Triple

T32347485
Position Surface form Disambiguated ID Type / Status
Subject Orlí Street Theatre E826501 entity
Predicate locatedOn P40 FINISHED
Object Orlí Street
Orlí Street is a street in Brno, Czech Republic, known for cultural venues including the modern Orlí Street Theatre associated with the Janáček Academy of Music and Performing Arts.
 E2026962 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: Orlí Street | Statement: [Orlí Street Theatre, locatedOn, Orlí Street]
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: Orlí Street
Triple: [Orlí Street Theatre, locatedOn, Orlí Street]
Generated description
Orlí Street is a street in Brno, Czech Republic, known for cultural venues including the modern Orlí Street Theatre associated with the Janáček Academy of Music and Performing Arts.

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_69f34914dfc48190a390cd0720d9e86f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6be536f8081908d1a5b26e5edc091 completed May 3, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c65c56f0819083545dbf55f31f19 completed June 19, 2026, 4:32 a.m.
NEDg Description generation batch_6a34c6c79e9881909dd398413eff8a9d completed June 19, 2026, 4:34 a.m.
NED2 Entity disambiguation (via description) batch_6a34c733dadc819090dfe76aae531d10 completed June 19, 2026, 4:36 a.m.
Created at: May 1, 2026, 12:48 a.m.