Triple

T37918113
Position Surface form Disambiguated ID Type / Status
Subject Holly Goldberg Sloan E945879 entity
Predicate wrote P2831 FINISHED
Object One-Third Nerd
One-Third Nerd is a humorous and heartfelt middle-grade novel about three siblings navigating family changes, friendship, and a beloved pet with problems, written by Holly Goldberg Sloan.
 E2247941 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: One-Third Nerd | Statement: [Holly Goldberg Sloan, wrote, One-Third Nerd]
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: One-Third Nerd
Triple: [Holly Goldberg Sloan, wrote, One-Third Nerd]
Generated description
One-Third Nerd is a humorous and heartfelt middle-grade novel about three siblings navigating family changes, friendship, and a beloved pet with problems, written by Holly Goldberg Sloan.

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_69f76ef2ebd88190be5229f2621070b3 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd77c1388190aaa5c2f9b7c2a9d5 completed May 6, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a410cd0af788190879149a313b7c40f completed June 28, 2026, noon
NEDg Description generation batch_6a410d8565e881908a8cd7eed4428c3f completed June 28, 2026, 12:03 p.m.
NED2 Entity disambiguation (via description) batch_6a410e054cd481909e7007161a894782 completed June 28, 2026, 12:05 p.m.
Created at: May 3, 2026, 4:20 p.m.