Triple

T24388186
Position Surface form Disambiguated ID Type / Status
Subject Julia Whelan E614807 entity
Predicate notableWork P4 FINISHED
Object My Oxford Year
My Oxford Year is a contemporary romance novel by Julia Whelan that follows an American Rhodes Scholar whose academic ambitions are complicated by an unexpected love affair at Oxford University.
 E1632739 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: My Oxford Year | Statement: [Julia Whelan, notableWork, My Oxford Year]
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: My Oxford Year
Triple: [Julia Whelan, notableWork, My Oxford Year]
Generated description
My Oxford Year is a contemporary romance novel by Julia Whelan that follows an American Rhodes Scholar whose academic ambitions are complicated by an unexpected love affair at Oxford University.

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_69e2d7e362e481909e32fe4ef8269d4f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29456cc548190bb92b750fd2d04af completed April 29, 2026, 11:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd68040b4819083bd2f0510e7aea6 completed May 22, 2026, 4:07 a.m.
NEDg Description generation batch_6a0fd757847081909f0c5e77d4dd97c7 completed May 22, 2026, 4:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd87ea3648190923d6f14c978f461 completed May 22, 2026, 4:15 a.m.
Created at: April 18, 2026, 2:03 a.m.