Triple

T33088937
Position Surface form Disambiguated ID Type / Status
Subject British motor industry E846716 entity
Predicate industryAssociation P19086 FINISHED
Object Motor Industry Research Association
The Motor Industry Research Association is a UK-based organization that conducts research, testing, and development services to support and advance the automotive sector.
E2035905 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: Motor Industry Research Association | Statement: [British motor industry, industryAssociation, Motor Industry Research Association]
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: Motor Industry Research Association
Triple: [British motor industry, industryAssociation, Motor Industry Research Association]
Generated description
The Motor Industry Research Association is a UK-based organization that conducts research, testing, and development services to support and advance the automotive sector.

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_69f3495590dc8190aa04f3dec74ce976 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d62443288190b7bc18d8f62c286e completed May 3, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34f026c81481909a6e49f03dde90c6 completed June 19, 2026, 7:30 a.m.
NEDg Description generation batch_6a34ffda4924819095b4a76ed9e5a3c3 completed June 19, 2026, 8:37 a.m.
NED2 Entity disambiguation (via description) batch_6a3500be2b44819089b389b1843bf4d1 completed June 19, 2026, 8:41 a.m.
Created at: May 1, 2026, 1:26 a.m.