Triple

T34115484
Position Surface form Disambiguated ID Type / Status
Subject Jill Krementz E874958 entity
Predicate notableWork P4 FINISHED
Object The Writer's Desk
The Writer's Desk is a photography book by Jill Krementz that presents intimate portraits of authors in their writing spaces.
 E2083339 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: The Writer's Desk | Statement: [Jill Krementz, notableWork, The Writer's Desk]
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: The Writer's Desk
Triple: [Jill Krementz, notableWork, The Writer's Desk]
Generated description
The Writer's Desk is a photography book by Jill Krementz that presents intimate portraits of authors in their writing spaces.

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_69f349a9271c81909576994c9ef7b179 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70cb880008190bc1ca79d89580949 completed May 3, 2026, 8:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36b76d410881908099c41b5530d4ef completed June 20, 2026, 3:53 p.m.
NEDg Description generation batch_6a36bb3f607c8190a3f49cbcbd3e1eed completed June 20, 2026, 4:09 p.m.
NED2 Entity disambiguation (via description) batch_6a36bd4560a081908ff4f8379d8d071d completed June 20, 2026, 4:18 p.m.
Created at: May 1, 2026, 1:53 a.m.