Triple

T37367622
Position Surface form Disambiguated ID Type / Status
Subject Swedish television industry E927754 entity
Predicate majorCommercialBroadcaster P201462 FINISHED
Object MTV Sweden
MTV Sweden was a Swedish version of the international MTV music and entertainment television channel, targeting Swedish audiences with localized programming and popular international content.
E2223226 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: MTV Sweden | Statement: [Swedish television industry, majorCommercialBroadcaster, MTV Sweden]
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: MTV Sweden
Triple: [Swedish television industry, majorCommercialBroadcaster, MTV Sweden]
Generated description
MTV Sweden was a Swedish version of the international MTV music and entertainment television channel, targeting Swedish audiences with localized programming and popular international content.

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_69f76eb820248190a5c395ca50ad002a completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fff8f9c6608190b42da7e73254f592 completed May 10, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a406ceb9b188190935deb613c4b4f78 completed June 28, 2026, 12:38 a.m.
NEDg Description generation batch_6a406d533600819091943cc903e90fac completed June 28, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_6a406dde8e30819082893b2e724b1424 completed June 28, 2026, 12:42 a.m.
Created at: May 3, 2026, 4:16 p.m.