Triple

T38375804
Position Surface form Disambiguated ID Type / Status
Subject Boston Globe–Horn Book Award E893618 entity
Predicate presentedBy P83 FINISHED
Object The Horn Book Magazine
The Horn Book Magazine is a long-running, influential American periodical devoted to reviewing and discussing children’s and young adult literature.
 E2267794 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: The Horn Book Magazine | Statement: [Boston Globe–Horn Book Award, presentedBy, The Horn Book Magazine]
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: The Horn Book Magazine
Triple: [Boston Globe–Horn Book Award, presentedBy, The Horn Book Magazine]
Generated description
The Horn Book Magazine is a long-running, influential American periodical devoted to reviewing and discussing children’s and young adult literature.

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_69f76e4b1f748190a380696a16eae4a2 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fcccface2c8190a944125c9742a561 completed May 7, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b2a0e1a481908f9d7f257a7bad2b completed June 28, 2026, 11:47 p.m.
NEDg Description generation batch_6a41b3aad0308190a8b1aea3b38ddc18 completed June 28, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_6a41b4aff75081909d0946a1c0992447 completed June 28, 2026, 11:56 p.m.
Created at: May 3, 2026, 4:31 p.m.