Triple

T36189751
Position Surface form Disambiguated ID Type / Status
Subject Blondie (film series) E1046953 entity
Predicate hasPart P35 FINISHED
Object Life with Blondie
Life with Blondie is a 1945 American comedy film in the Blondie series, following the humorous domestic adventures of Dagwood Bumstead, his wife Blondie, and their family.
E2182644 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: Life with Blondie | Statement: [Blondie (film series), hasPart, Life with Blondie]
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: Life with Blondie
Triple: [Blondie (film series), hasPart, Life with Blondie]
Generated description
Life with Blondie is a 1945 American comedy film in the Blondie series, following the humorous domestic adventures of Dagwood Bumstead, his wife Blondie, and their family.

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_69f76e3d4fbc81908c159c7beeb4ce00 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b52b97748190bc14092bff61beb0 completed May 3, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b41babbc819095b993b7bbb4211a completed June 22, 2026, 10:15 p.m.
NEDg Description generation batch_6a39b7589c8c81909da9923396fefe6e completed June 22, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a39bc45e43881908e3374a9e7d28cfb completed June 22, 2026, 10:50 p.m.
Created at: May 3, 2026, 4:08 p.m.