Triple

T27715095
Position Surface form Disambiguated ID Type / Status
Subject Taylor pork roll E698794 entity
Predicate developedBy P73 FINISHED
Object John Taylor
John Taylor was a 19th-century American businessman and food manufacturer best known for creating the New Jersey breakfast meat specialty known as Taylor pork roll.
E698793 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 Taylor | Statement: [Taylor pork roll, developedBy, John Taylor]
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 Taylor
Triple: [Taylor pork roll, developedBy, John Taylor]
Generated description
John Taylor was a 19th-century American businessman and food manufacturer best known for creating the New Jersey breakfast meat specialty known as Taylor pork roll.

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_69ef590f655c81909f93893b3b3219b2 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f635cfa6088190aae92d408c036238 completed May 2, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e46395e48190bcf054f958449f0c completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e528463c819087d479b960e660d2 completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e58a24a08190baec56a49e9f24e8 completed May 24, 2026, 11:48 a.m.
Created at: April 27, 2026, 3:04 p.m.