Triple

T23492525
Position Surface form Disambiguated ID Type / Status
Subject murder of Joseph Rosen E570714 entity
Predicate victim P870 FINISHED
Object Joseph Rosen
Joseph Rosen was a Brooklyn candy store owner who became a notable victim of the Murder, Inc. crime syndicate in 1936.
E1858910 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: Joseph Rosen | Statement: [murder of Joseph Rosen, victim, Joseph Rosen]
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: Joseph Rosen
Triple: [murder of Joseph Rosen, victim, Joseph Rosen]
Generated description
Joseph Rosen was a Brooklyn candy store owner who became a notable victim of the Murder, Inc. crime syndicate in 1936.

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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7dd56408190b459077e433ed1c3 completed April 29, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2588efb8848190af8e46d0ca7746a2 completed June 7, 2026, 3:06 p.m.
NEDg Description generation batch_6a258d5c870881909c75fab5ef8093bd completed June 7, 2026, 3:25 p.m.
NED2 Entity disambiguation (via description) batch_6a2591728844819099129a16cb37bd69 completed June 7, 2026, 3:42 p.m.
Created at: April 17, 2026, 6:05 p.m.