Triple

T24319885
Position Surface form Disambiguated ID Type / Status
Subject Penny Singleton E612929 entity
Predicate performedIn P795 FINISHED
Object Blondie's Big Moment
Blondie's Big Moment is a 1947 American comedy film in the long-running "Blondie" series, starring Penny Singleton as the comic-strip heroine Blondie Bumstead.
E1639133 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: Blondie's Big Moment | Statement: [Penny Singleton, performedIn, Blondie's Big Moment]
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: Blondie's Big Moment
Triple: [Penny Singleton, performedIn, Blondie's Big Moment]
Generated description
Blondie's Big Moment is a 1947 American comedy film in the long-running "Blondie" series, starring Penny Singleton as the comic-strip heroine Blondie Bumstead.

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_69e2d7da491c8190b6e6218af50923db completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292aa63fc8190a874367c9010f283 completed April 29, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee59bc708190a190f1e19386a913 completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0ff0c57b088190b031ea186a987e32 completed May 22, 2026, 5:59 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff16636008190a4267f6b8d8e3bb2 completed May 22, 2026, 6:02 a.m.
Created at: April 18, 2026, 1:48 a.m.