Triple

T37910409
Position Surface form Disambiguated ID Type / Status
Subject The Affairs of Annabel E945668 entity
Predicate followedBy P78 FINISHED
Object Annabel Takes a Tour
Annabel Takes a Tour is a 1938 American comedy film starring Lucille Ball as the publicity-prone actress Annabel Allison in a sequel to The Affairs of Annabel.
E2248480 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: Annabel Takes a Tour | Statement: [The Affairs of Annabel, followedBy, Annabel Takes a Tour]
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: Annabel Takes a Tour
Triple: [The Affairs of Annabel, followedBy, Annabel Takes a Tour]
Generated description
Annabel Takes a Tour is a 1938 American comedy film starring Lucille Ball as the publicity-prone actress Annabel Allison in a sequel to The Affairs of Annabel.

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_69f76ef20bb0819088b5b6ceecb0b8fc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd5d2a308190a78f443f7ba85907 completed May 6, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a410ccc973c8190b53b11c6c0af320c completed June 28, 2026, noon
NEDg Description generation batch_6a410d70ba0c8190bdcab9e762c92884 completed June 28, 2026, 12:02 p.m.
NED2 Entity disambiguation (via description) batch_6a410e3dd828819099fc3a413bcfbeb9 completed June 28, 2026, 12:06 p.m.
Created at: May 3, 2026, 4:20 p.m.