Triple

T35856113
Position Surface form Disambiguated ID Type / Status
Subject Michael Meeropol E1036508 entity
Predicate birthName P65 FINISHED
Object Michael Rosenberg
Michael Rosenberg is an American economist and academic best known as one of the sons of Julius and Ethel Rosenberg, the couple executed for espionage during the Cold War.
E2244774 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: Michael Rosenberg | Statement: [Michael Meeropol, birthName, Michael Rosenberg]
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: Michael Rosenberg
Triple: [Michael Meeropol, birthName, Michael Rosenberg]
Generated description
Michael Rosenberg is an American economist and academic best known as one of the sons of Julius and Ethel Rosenberg, the couple executed for espionage during the Cold War.

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_69f76e1b4aa481909630373171eb5ec6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a97113b88190a7366650c77d4eba completed May 3, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40fb5fcddc81909d5bdb15468b7f40 completed June 28, 2026, 10:45 a.m.
NEDg Description generation batch_6a40fc8d1b008190b9bff52786f646a3 completed June 28, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a40fcf8f3a88190803a9504da1fdd3d completed June 28, 2026, 10:52 a.m.
Created at: May 3, 2026, 4:06 p.m.