Triple

T27669520
Position Surface form Disambiguated ID Type / Status
Subject Main Street Hub E697621 entity
Predicate foundedBy P104 FINISHED
Object Andrew Allison
Andrew Allison is an entrepreneur best known as a co-founder of Main Street Hub, a company that provided marketing and customer relationship management services for local businesses.
 E1789747 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: Andrew Allison | Statement: [Main Street Hub, foundedBy, Andrew Allison]
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: Andrew Allison
Triple: [Main Street Hub, foundedBy, Andrew Allison]
Generated description
Andrew Allison is an entrepreneur best known as a co-founder of Main Street Hub, a company that provided marketing and customer relationship management services for local businesses.

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_69ef590d458c81909583290c3cd0478b completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f634a807c88190bb549a04e16bfd8d completed May 2, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ec9e61188190a7d032077d05ddca completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ed49266881909fd55a7028ad6a1f completed May 24, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee215b4c8190aeef56575c0c0015 completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 2:40 p.m.