Triple

T35738312
Position Surface form Disambiguated ID Type / Status
Subject Moshe Sofer E1032956 entity
Predicate notableWork P4 FINISHED
Object Chasam Sofer on Shas
Chasam Sofer on Shas is a classic multi-volume collection of Talmudic responsa and novellae by Rabbi Moshe Sofer, widely studied in traditional yeshivas for its rigorous halachic analysis and conservative rabbinic outlook.
E2153204 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: Chasam Sofer on Shas | Statement: [Moshe Sofer, notableWork, Chasam Sofer on Shas]
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: Chasam Sofer on Shas
Triple: [Moshe Sofer, notableWork, Chasam Sofer on Shas]
Generated description
Chasam Sofer on Shas is a classic multi-volume collection of Talmudic responsa and novellae by Rabbi Moshe Sofer, widely studied in traditional yeshivas for its rigorous halachic analysis and conservative rabbinic outlook.

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_69f76e10e59081908d81ad9ce22f40b6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a168b33081909e20588b6c65ac6d completed May 3, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387d2304408190b1220cc03d5ba2c2 completed June 22, 2026, 12:09 a.m.
NEDg Description generation batch_6a387f0e8ca88190b2542f3e8bb09305 completed June 22, 2026, 12:17 a.m.
NED2 Entity disambiguation (via description) batch_6a387f873ab08190a7e792db20e86743 completed June 22, 2026, 12:19 a.m.
Created at: May 3, 2026, 4:05 p.m.