Triple

T27783493
Position Surface form Disambiguated ID Type / Status
Subject The Prize Winner of Defiance, Ohio E699396 entity
Predicate basedOnAuthor P2806 FINISHED
Object Terry Ryan
Terry Ryan was an American writer and humorist best known for her memoir "The Prize Winner of Defiance, Ohio," which recounts her mother's success in jingle-writing contests to support their large family.
E1788569 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: Terry Ryan | Statement: [The Prize Winner of Defiance, Ohio, basedOnAuthor, Terry Ryan]
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: Terry Ryan
Triple: [The Prize Winner of Defiance, Ohio, basedOnAuthor, Terry Ryan]
Generated description
Terry Ryan was an American writer and humorist best known for her memoir "The Prize Winner of Defiance, Ohio," which recounts her mother's success in jingle-writing contests to support their large family.

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_69ef6a4b5a9081909c9111396c2be3d2 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f637d083408190bfc124e8a3f60af7 completed May 2, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecc61728819095cad91e0fa3ab4f completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ed68ab588190a2247672cc7818d8 completed May 24, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee55079881908070830187dedd6d completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 5:11 p.m.