Triple

T31084072
Position Surface form Disambiguated ID Type / Status
Subject Love on Toast E792178 entity
Predicate castMember P1668 FINISHED
Object Frank Mills
Frank Mills was a British character actor known for his numerous supporting roles in film and television throughout the mid-20th century.
E1944428 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: Frank Mills | Statement: [Love on Toast, castMember, Frank Mills]
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: Frank Mills
Triple: [Love on Toast, castMember, Frank Mills]
Generated description
Frank Mills was a British character actor known for his numerous supporting roles in film and television throughout the mid-20th century.

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_69f224ce48348190bd0fc23f656ed683 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695fc607c8190a5735f3b4bded7db completed May 3, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b2ba15c81909db4bb602d1c4353 completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292cb9db7081909a3f2ff33bd3a2b4 completed June 10, 2026, 9:22 a.m.
NED2 Entity disambiguation (via description) batch_6a292d2fe9248190979437db9ab64ed8 completed June 10, 2026, 9:24 a.m.
Created at: April 29, 2026, 9:02 p.m.