Triple

T35413837
Position Surface form Disambiguated ID Type / Status
Subject Uriel Weinreich E1023583 entity
Predicate father P120 FINISHED
Object Max Weinreich
Max Weinreich was a prominent Jewish linguist and historian best known as a co-founder of the YIVO Institute for Jewish Research and a leading scholar of the Yiddish language.
E2157480 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: Max Weinreich | Statement: [Uriel Weinreich, father, Max Weinreich]
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: Max Weinreich
Triple: [Uriel Weinreich, father, Max Weinreich]
Generated description
Max Weinreich was a prominent Jewish linguist and historian best known as a co-founder of the YIVO Institute for Jewish Research and a leading scholar of the Yiddish language.

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_69f76df54bac8190bd0d3b0eb35cda5f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7956a3444819093748feaf7c4a7aa completed May 3, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a389bfb48b88190ace98cefcbeb937f completed June 22, 2026, 2:20 a.m.
NEDg Description generation batch_6a389ca938d0819094ce32b9a0ca8aa3 completed June 22, 2026, 2:23 a.m.
NED2 Entity disambiguation (via description) batch_6a389d7b23748190993070e1405d79de completed June 22, 2026, 2:27 a.m.
Created at: May 3, 2026, 4:03 p.m.