Triple

T28858177
Position Surface form Disambiguated ID Type / Status
Subject Tim Birkin E728792 entity
Predicate nobleTitle P914 FINISHED
Object 2nd Baronet Birkin
2nd Baronet Birkin is the hereditary baronetcy title held by British racing driver Sir Henry "Tim" Birkin, a famed member of the "Bentley Boys" in the interwar era.
E1836169 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: 2nd Baronet Birkin | Statement: [Tim Birkin, nobleTitle, 2nd Baronet Birkin]
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: 2nd Baronet Birkin
Triple: [Tim Birkin, nobleTitle, 2nd Baronet Birkin]
Generated description
2nd Baronet Birkin is the hereditary baronetcy title held by British racing driver Sir Henry "Tim" Birkin, a famed member of the "Bentley Boys" in the interwar era.

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_69f0319f4e5481909e4c439dbe8be940 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65a14eaa081908113d246dbaf86dd completed May 2, 2026, 8:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bbbfd1b08190840af4a4d5f64c70 completed June 7, 2026, 12:30 a.m.
NEDg Description generation batch_6a24c119da5c81909d6e30197c1c496a completed June 7, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_6a24c4f2fd5c8190a9ab30778df67cfb completed June 7, 2026, 1:10 a.m.
Created at: April 28, 2026, 6:46 a.m.