Triple

T37147790
Position Surface form Disambiguated ID Type / Status
Subject Chok Yaakov E920286 entity
Predicate author P4 FINISHED
Object Rabbi Yaakov Reischer
Rabbi Yaakov Reischer was a prominent 17th–18th century Ashkenazi rabbi and halachic authority, best known for his influential rabbinic responsa and commentaries on Jewish law.
E2221970 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: Rabbi Yaakov Reischer | Statement: [Chok Yaakov, author, Rabbi Yaakov Reischer]
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: Rabbi Yaakov Reischer
Triple: [Chok Yaakov, author, Rabbi Yaakov Reischer]
Generated description
Rabbi Yaakov Reischer was a prominent 17th–18th century Ashkenazi rabbi and halachic authority, best known for his influential rabbinic responsa and commentaries on Jewish law.

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_69f76e9f87c08190b4c8f7fafbd8345a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb30899618819098b0826c4a544bef completed May 6, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406376d4f08190baf8d1e368818760 completed June 27, 2026, 11:57 p.m.
NEDg Description generation batch_6a4064c5b5f88190bb07582555831f32 completed June 28, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a40655bd8d881908a0824fbd19562cd completed June 28, 2026, 12:05 a.m.
Created at: May 3, 2026, 4:15 p.m.