Triple

T31697213
Position Surface form Disambiguated ID Type / Status
Subject Yeshivat Har Etzion E808948 entity
Predicate founder P104 FINISHED
Object Yehuda Amital
Yehuda Amital was a prominent Israeli Orthodox rabbi, educator, and religious-Zionist leader who played a key role in shaping modern Torah study and ideology in Israel.
E1994902 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: Yehuda Amital | Statement: [Yeshivat Har Etzion, founder, Yehuda Amital]
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: Yehuda Amital
Triple: [Yeshivat Har Etzion, founder, Yehuda Amital]
Generated description
Yehuda Amital was a prominent Israeli Orthodox rabbi, educator, and religious-Zionist leader who played a key role in shaping modern Torah study and ideology in Israel.

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_69f348de914081909fc8edff56f34dbe completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aaa66e1081909afb3623b110db70 completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0baefe04819089493bcfe6d2de43 completed June 14, 2026, 8:14 p.m.
NEDg Description generation batch_6a2f0deba97c8190a87d85dcfe75d231 completed June 14, 2026, 8:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2f0e0c18588190b45787723d1dcf40 completed June 14, 2026, 8:24 p.m.
Created at: April 30, 2026, 11:10 p.m.