Triple

T34067285
Position Surface form Disambiguated ID Type / Status
Subject On Kawara I Went series E873661 entity
Predicate relatedWork P37 FINISHED
Object On Kawara I Got Up series
The "On Kawara I Got Up" series is a conceptual art project in which On Kawara documented his daily life by sending postcards stamped with the exact time he woke up each day.
E2074456 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: On Kawara I Got Up series | Statement: [On Kawara I Went series, relatedWork, On Kawara I Got Up series]
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: On Kawara I Got Up series
Triple: [On Kawara I Went series, relatedWork, On Kawara I Got Up series]
Generated description
The "On Kawara I Got Up" series is a conceptual art project in which On Kawara documented his daily life by sending postcards stamped with the exact time he woke up each day.

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_69f349a4af208190afa14888f9c9fb9d completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70ba50a188190b595083c3acd350a completed May 3, 2026, 8:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36c1b8df588190bc07d7e79bb8a7d5 completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c24f7ba081908bd581d1f7aa1d1c completed June 20, 2026, 4:39 p.m.
NED2 Entity disambiguation (via description) batch_6a36c4a9f96481909d318fd78827a1f2 completed June 20, 2026, 4:49 p.m.
Created at: May 1, 2026, 1:52 a.m.