Triple

T30939083
Position Surface form Disambiguated ID Type / Status
Subject Jewish Fighting Organization in Vilna Ghetto E788208 entity
Predicate hasNotableMember P304 FINISHED
Object Chaim Lazar
Chaim Lazar was a Jewish resistance fighter and partisan leader from the Vilna Ghetto who later became known for documenting the history of Jewish armed resistance during the Holocaust.
E1951848 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: Chaim Lazar | Statement: [Jewish Fighting Organization in Vilna Ghetto, hasNotableMember, Chaim Lazar]
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: Chaim Lazar
Triple: [Jewish Fighting Organization in Vilna Ghetto, hasNotableMember, Chaim Lazar]
Generated description
Chaim Lazar was a Jewish resistance fighter and partisan leader from the Vilna Ghetto who later became known for documenting the history of Jewish armed resistance during the Holocaust.

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_69f224c0b7fc819090cb89df60d23653 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f692e6d7548190a7526bb4be28dc38 completed May 3, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2958f5052c81908cd9b32a73c6e0b3 completed June 10, 2026, 12:30 p.m.
NEDg Description generation batch_6a295991211c8190ac7a8656196b0760 completed June 10, 2026, 12:33 p.m.
NED2 Entity disambiguation (via description) batch_6a295d91f59c819096a9baa006e93830 completed June 10, 2026, 12:50 p.m.
Created at: April 29, 2026, 8:52 p.m.