Triple

T28620066
Position Surface form Disambiguated ID Type / Status
Subject MPEG-H E724356 entity
Predicate hasPart P35 FINISHED
Object MPEG-H Part 10
MPEG-H Part 10 is a component of the MPEG-H multimedia coding standard that defines a specific aspect of advanced audio-visual compression and delivery.
E724356 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: MPEG-H Part 10 | Statement: [MPEG-H, hasPart, MPEG-H Part 10]
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: MPEG-H Part 10
Triple: [MPEG-H, hasPart, MPEG-H Part 10]
Generated description
MPEG-H Part 10 is a component of the MPEG-H multimedia coding standard that defines a specific aspect of advanced audio-visual compression and delivery.

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_69f01d822ac08190932de59ec2268ed2 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6524892d4819088dd0ae5aab08dff completed May 2, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25378874808190ac293d4f53a8b6b4 completed June 7, 2026, 9:19 a.m.
NEDg Description generation batch_6a253b9227ec8190b3887b13af5938b3 completed June 7, 2026, 9:36 a.m.
NED2 Entity disambiguation (via description) batch_6a253fa2b67c8190a8ff6e0a1d129cd7 completed June 7, 2026, 9:53 a.m.
Created at: April 28, 2026, 4:33 a.m.