Triple

T34690191
Position Surface form Disambiguated ID Type / Status
Subject Poul Kjærholm E890869 entity
Predicate notableWork P4 FINISHED
Object PK80 daybed
The PK80 daybed is a minimalist, modernist lounge piece by Danish designer Poul Kjærholm, celebrated for its refined steel frame, leather upholstery, and sculptural simplicity.
E2108714 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: PK80 daybed | Statement: [Poul Kjærholm, notableWork, PK80 daybed]
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: PK80 daybed
Triple: [Poul Kjærholm, notableWork, PK80 daybed]
Generated description
The PK80 daybed is a minimalist, modernist lounge piece by Danish designer Poul Kjærholm, celebrated for its refined steel frame, leather upholstery, and sculptural simplicity.

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_6a3752f8a34c8190a4790585c7eae03a completed June 21, 2026, 2:56 a.m.
NEDg Description generation batch_6a37546c6edc8190bc5e80caf7bd7705 completed June 21, 2026, 3:03 a.m.
NED2 Entity disambiguation (via description) batch_6a3755525b3081909a941c144c63d56b completed June 21, 2026, 3:06 a.m.
Created at: May 1, 2026, 2:05 a.m.