Triple

T33578442
Position Surface form Disambiguated ID Type / Status
Subject David Kazhdan E860088 entity
Predicate notableStudent P4838 FINISHED
Object Shahar Mozes
Shahar Mozes is an Israeli mathematician known for his work in group theory, ergodic theory, and geometric group theory.
E2057481 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: Shahar Mozes | Statement: [David Kazhdan, notableStudent, Shahar Mozes]
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: Shahar Mozes
Triple: [David Kazhdan, notableStudent, Shahar Mozes]
Generated description
Shahar Mozes is an Israeli mathematician known for his work in group theory, ergodic theory, and geometric group theory.

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_69f3497d37848190afcbb5ef3f5c7376 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f76e085c81909d71d6f47853cd12 completed May 3, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35afe373f88190abc1119522549c35 completed June 19, 2026, 9:08 p.m.
NEDg Description generation batch_6a35b1830e288190a2344252b343b93f completed June 19, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_6a35b23a6abc8190ac650b3c0749a9a1 completed June 19, 2026, 9:18 p.m.
Created at: May 1, 2026, 1:40 a.m.