Triple

T34426222
Position Surface form Disambiguated ID Type / Status
Subject Grace Hawkins E883677 entity
Predicate setInWorkContext P41119 FINISHED
Object rural English village of Little Wallop
The rural English village of Little Wallop is the fictional, quintessentially quaint countryside setting of the British comedy film "Keeping Mum."
E2094737 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: rural English village of Little Wallop | Statement: [Grace Hawkins, setInWorkContext, rural English village of Little Wallop]
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: rural English village of Little Wallop
Triple: [Grace Hawkins, setInWorkContext, rural English village of Little Wallop]
Generated description
The rural English village of Little Wallop is the fictional, quintessentially quaint countryside setting of the British comedy film "Keeping Mum."

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_69f349c3dd2c819092cc9e64809f4a42 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f718e00dc88190994c42476239c27c completed May 3, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a370ddc10e88190b6d5e7eb6fb52f01 completed June 20, 2026, 10:02 p.m.
NEDg Description generation batch_6a370f7561048190a9789a707d241fa1 completed June 20, 2026, 10:08 p.m.
NED2 Entity disambiguation (via description) batch_6a370fd563e4819098a0cc75d251435b completed June 20, 2026, 10:10 p.m.
Created at: May 1, 2026, 2 a.m.