Triple

T23841001
Position Surface form Disambiguated ID Type / Status
Subject Amy Krouse Rosenthal E590986 entity
Predicate spouse P13 FINISHED
Object Jason Rosenthal
Jason Rosenthal is an American lawyer, speaker, and author known for his late wife Amy Krouse Rosenthal’s viral “You May Want to Marry My Husband” essay and his subsequent work on grief, resilience, and personal transformation.
E1622932 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: Jason Rosenthal | Statement: [Amy Krouse Rosenthal, spouse, Jason Rosenthal]
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: Jason Rosenthal
Triple: [Amy Krouse Rosenthal, spouse, Jason Rosenthal]
Generated description
Jason Rosenthal is an American lawyer, speaker, and author known for his late wife Amy Krouse Rosenthal’s viral “You May Want to Marry My Husband” essay and his subsequent work on grief, resilience, and personal transformation.

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_69e25d1de32c8190a907afe9c3d6cd6d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c88797d4819081831fd3f8822ef4 completed April 29, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0facf2bdb08190bc1b0c74b2d974a8 completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fadbe98a08190bcde092c36f2159a completed May 22, 2026, 1:13 a.m.
NED2 Entity disambiguation (via description) batch_6a0fae34bb948190b8f936d8f47d7c41 completed May 22, 2026, 1:15 a.m.
Created at: April 17, 2026, 8:08 p.m.