Triple

T27520507
Position Surface form Disambiguated ID Type / Status
Subject Jewish School of Paris E694693 entity
Predicate notableMember P10 FINISHED
Object Chaïm Goldberg
Chaïm Goldberg was a Polish-born Jewish painter, sculptor, and printmaker best known for his vivid depictions of shtetl life and the Jewish experience before and after the Holocaust.
E1842269 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: Chaïm Goldberg | Statement: [Jewish School of Paris, notableMember, Chaïm Goldberg]
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: Chaïm Goldberg
Triple: [Jewish School of Paris, notableMember, Chaïm Goldberg]
Generated description
Chaïm Goldberg was a Polish-born Jewish painter, sculptor, and printmaker best known for his vivid depictions of shtetl life and the Jewish experience before and after the Holocaust.

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_69ef538550208190aa9de8e2cb260d93 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f2ba2b88190962819631042d02d completed May 2, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec14e6388190ba6b15741ad914b8 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f07e3a54819090dc0d92cee92204 completed June 7, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a24f56a17a48190a309ea59a2ebf4d1 completed June 7, 2026, 4:36 a.m.
Created at: April 27, 2026, 1:21 p.m.