Triple

T34339269
Position Surface form Disambiguated ID Type / Status
Subject MVPA Award E881239 entity
Predicate alsoKnownAs P39 FINISHED
Object Music Video Production Association Award
The Music Video Production Association Award is an industry honor recognizing outstanding achievement in the creation and production of music videos.
E2091011 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: Music Video Production Association Award | Statement: [MVPA Award, alsoKnownAs, Music Video Production Association Award]
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: Music Video Production Association Award
Triple: [MVPA Award, alsoKnownAs, Music Video Production Association Award]
Generated description
The Music Video Production Association Award is an industry honor recognizing outstanding achievement in the creation and production of music videos.

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_69f349bc55e881908c8e338ef76b0043 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f713c652448190b3cab6c38f82f52c completed May 3, 2026, 9:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36f9df678481909cd150924dddfeb3 completed June 20, 2026, 8:36 p.m.
NEDg Description generation batch_6a36fab9d4448190a49caae3e8f7c561 completed June 20, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_6a36fb6882fc8190bd69194e3eabeb8f completed June 20, 2026, 8:43 p.m.
Created at: May 1, 2026, 1:58 a.m.