Triple

T35579510
Position Surface form Disambiguated ID Type / Status
Subject Rabbi Shlomo Eiger E1028179 entity
Predicate name P16 FINISHED
Object Shlomo Eiger
Shlomo Eiger was a prominent 19th-century Polish rabbi and Talmudic scholar, known as the son of Rabbi Akiva Eiger and for his halachic writings and leadership in the Jewish community of Posen.
E2157965 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: Shlomo Eiger | Statement: [Rabbi Shlomo Eiger, name, Shlomo Eiger]
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: Shlomo Eiger
Triple: [Rabbi Shlomo Eiger, name, Shlomo Eiger]
Generated description
Shlomo Eiger was a prominent 19th-century Polish rabbi and Talmudic scholar, known as the son of Rabbi Akiva Eiger and for his halachic writings and leadership in the Jewish community of Posen.

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_69f76e0386688190b931bacdc145938c completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79e826f248190a8b8e9344f3f15fc completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a389c02049c8190b7103e2c0fc73f95 completed June 22, 2026, 2:20 a.m.
NEDg Description generation batch_6a389d901c048190af8cbb4eb5fca156 completed June 22, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_6a389e5407b48190a8f1610e6ba216b4 completed June 22, 2026, 2:30 a.m.
Created at: May 3, 2026, 4:04 p.m.