Triple

T29626876
Position Surface form Disambiguated ID Type / Status
Subject Basil Hood E755166 entity
Predicate notableWork P4 FINISHED
Object Merrie England
Merrie England is a popular Edwardian-era English comic opera, with music by Edward German and a libretto by Basil Hood, that nostalgically romanticizes the Tudor court of Queen Elizabeth I.
E1876182 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: Merrie England | Statement: [Basil Hood, notableWork, Merrie England]
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: Merrie England
Triple: [Basil Hood, notableWork, Merrie England]
Generated description
Merrie England is a popular Edwardian-era English comic opera, with music by Edward German and a libretto by Basil Hood, that nostalgically romanticizes the Tudor court of Queen Elizabeth I.

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_69f0ef86b6ec8190a87fff07fd983b1e completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66e61866881908f1497a7ceb782bc completed May 2, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26617263bc8190af48491a1001deb3 completed June 8, 2026, 6:30 a.m.
NEDg Description generation batch_6a26656a3cdc81908287a8a2145d6cc6 completed June 8, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a266a6166a08190a3ec83291c005e7b completed June 8, 2026, 7:08 a.m.
Created at: April 28, 2026, 6:38 p.m.