Triple

T34690174
Position Surface form Disambiguated ID Type / Status
Subject Poul Kjærholm E890869 entity
Predicate birthPlace P1 FINISHED
Object Østervrå, Denmark
Østervrå, Denmark is a small town in the North Jutland region known as the birthplace of renowned Danish furniture designer Poul Kjærholm.
E2110978 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: Østervrå, Denmark | Statement: [Poul Kjærholm, birthPlace, Østervrå, Denmark]
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: Østervrå, Denmark
Triple: [Poul Kjærholm, birthPlace, Østervrå, Denmark]
Generated description
Østervrå, Denmark is a small town in the North Jutland region known as the birthplace of renowned Danish furniture designer Poul Kjærholm.

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_69f349db7ab8819086808e833f472871 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72350dd7881908a30f0e2e230931c completed May 3, 2026, 10:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37661f7e34819086895f82d892314e completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a3766c62020819090092f8f0de60644 completed June 21, 2026, 4:21 a.m.
NED2 Entity disambiguation (via description) batch_6a37673026e881908b26f42f12f81b2f completed June 21, 2026, 4:23 a.m.
Created at: May 1, 2026, 2:05 a.m.