Triple

T38301650
Position Surface form Disambiguated ID Type / Status
Subject Primetime Emmy Award for Outstanding Picture Editing for a Structured Reality or Competition Program E1032236 entity
Predicate relatedTo P37 FINISHED
Object Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program
The Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program is a television industry honor recognizing exceptional editing work in unscripted, non-structured reality series.
E2266156 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: Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program | Statement: [Primetime Emmy Award for Outstanding Picture Editing for a Structured Reality or Competition Program, relatedTo, Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program]
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: Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program
Triple: [Primetime Emmy Award for Outstanding Picture Editing for a Structured Reality or Competition Program, relatedTo, Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program]
Generated description
The Primetime Emmy Award for Outstanding Picture Editing for an Unstructured Reality Program is a television industry honor recognizing exceptional editing work in unscripted, non-structured reality series.

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_69f76e0f2084819091299d021625c3fe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc61afcd48190bd2bcc1444173561 completed May 7, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41a7df92988190a843a0b1774d786c completed June 28, 2026, 11:01 p.m.
NEDg Description generation batch_6a41a951479c8190aa3466326a6107b2 completed June 28, 2026, 11:08 p.m.
NED2 Entity disambiguation (via description) batch_6a41a9f0b9748190a604e440751cbf67 completed June 28, 2026, 11:10 p.m.
Created at: May 3, 2026, 4:30 p.m.