Triple

T32817870
Position Surface form Disambiguated ID Type / Status
Subject Mackay E839350 entity
Predicate hasNotableBearer P458 FINISHED
Object John Henry Mackay
John Henry Mackay was a Scottish-born German writer and individualist anarchist known for his poetry, novels, and advocacy of libertarian and homosexual rights in the late 19th and early 20th centuries.
E2029508 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: John Henry Mackay | Statement: [Mackay, hasNotableBearer, John Henry Mackay]
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: John Henry Mackay
Triple: [Mackay, hasNotableBearer, John Henry Mackay]
Generated description
John Henry Mackay was a Scottish-born German writer and individualist anarchist known for his poetry, novels, and advocacy of libertarian and homosexual rights in the late 19th and early 20th centuries.

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdd27c44819091d45e31f4b67e64 completed May 3, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d24dac6c8190afc60eab748a2a26 completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d367d9308190854b8ea6f3e9fedd completed June 19, 2026, 5:28 a.m.
NED2 Entity disambiguation (via description) batch_6a34d3ab5e98819091f34300bf83621d completed June 19, 2026, 5:29 a.m.
Created at: May 1, 2026, 1:15 a.m.