Triple

T36819552
Position Surface form Disambiguated ID Type / Status
Subject Maharsha E909841 entity
Predicate alsoKnownAs P39 FINISHED
Object Rabbi Shmuel Eidels
Rabbi Shmuel Eidels, known by the acronym Maharsha, was a prominent 16th–17th century Talmudic scholar renowned for his influential commentaries on the Talmud and Rashi/Tosafot.
E2201953 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 Shmuel Eidels | Statement: [Maharsha, alsoKnownAs, Rabbi Shmuel Eidels]
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 Shmuel Eidels
Triple: [Maharsha, alsoKnownAs, Rabbi Shmuel Eidels]
Generated description
Rabbi Shmuel Eidels, known by the acronym Maharsha, was a prominent 16th–17th century Talmudic scholar renowned for his influential commentaries on the Talmud and Rashi/Tosafot.

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_69f76e7dd13c81908c60b05adb49eeb5 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7ca96859c81909e6a6d840b13b071 completed May 3, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dde636064819098c5bbfe9ad518cc completed June 26, 2026, 2:05 a.m.
NEDg Description generation batch_6a3ddefde7808190910be7eedc4a82e0 completed June 26, 2026, 2:07 a.m.
NED2 Entity disambiguation (via description) batch_6a3df5ed1e648190b6ecf44bae16a7a8 completed June 26, 2026, 3:45 a.m.
Created at: May 3, 2026, 4:13 p.m.