Triple

T27781691
Position Surface form Disambiguated ID Type / Status
Subject The Little Vampire E699348 entity
Predicate screenwriter P2831 FINISHED
Object Angela Sommer-Bodenburg
Angela Sommer-Bodenburg is a German author best known for creating the popular children's book series "The Little Vampire," which has been adapted into various films and television productions.
E1826361 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: Angela Sommer-Bodenburg | Statement: [The Little Vampire, screenwriter, Angela Sommer-Bodenburg]
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: Angela Sommer-Bodenburg
Triple: [The Little Vampire, screenwriter, Angela Sommer-Bodenburg]
Generated description
Angela Sommer-Bodenburg is a German author best known for creating the popular children's book series "The Little Vampire," which has been adapted into various films and television productions.

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_69ef6a4b5a9081909c9111396c2be3d2 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f637cf6d248190a86a85cfeba3719b completed May 2, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6bff9ac8190aed95ae1bc50d66e completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cbaaa69348190a4e8de0490e66edf completed May 31, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a1cbb5d90ec819093705eae50314f33 completed May 31, 2026, 10:51 p.m.
Created at: April 27, 2026, 5:10 p.m.