Triple

T27008465
Position Surface form Disambiguated ID Type / Status
Subject The Return of the Dancing Master E680312 entity
Predicate originalTitle P65 FINISHED
Object Danslärarens återkomst
Danslärarens återkomst is a crime novel by Swedish author Henning Mankell featuring detective Stefan Lindman as he investigates the murder of a retired dance teacher with a Nazi past.
E1750082 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: Danslärarens återkomst | Statement: [The Return of the Dancing Master, originalTitle, Danslärarens återkomst]
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: Danslärarens återkomst
Triple: [The Return of the Dancing Master, originalTitle, Danslärarens återkomst]
Generated description
Danslärarens återkomst is a crime novel by Swedish author Henning Mankell featuring detective Stefan Lindman as he investigates the murder of a retired dance teacher with a Nazi past.

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_69eeeb53939c8190bd431f32b060f01f completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f621d4667081909d0008559850bc10 completed May 2, 2026, 4:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229c260c48190be06e095a87efa9e completed May 23, 2026, 10:27 p.m.
NEDg Description generation batch_6a122a3ae1748190abe3dcd0c8036cfa completed May 23, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a122b06fe7c8190b61a01c92b4c790b completed May 23, 2026, 10:32 p.m.
Created at: April 27, 2026, 7:02 a.m.