Triple

T19318106
Position Surface form Disambiguated ID Type / Status
Subject Pier 1 Imports E483150 entity
Predicate foundedBy P104 FINISHED
Object Charles D. Tandy
Charles D. Tandy was an American businessman and retail entrepreneur best known for building the Tandy Corporation empire and expanding chains like RadioShack and Pier 1 Imports.
E2284128 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: Charles D. Tandy | Statement: [Pier 1 Imports, foundedBy, Charles D. Tandy]
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: Charles D. Tandy
Triple: [Pier 1 Imports, foundedBy, Charles D. Tandy]
Generated description
Charles D. Tandy was an American businessman and retail entrepreneur best known for building the Tandy Corporation empire and expanding chains like RadioShack and Pier 1 Imports.

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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e60d85046c81909d972a6b369b0c2b completed April 20, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a431e1fc5cc81909a820eb13bfeea28 completed June 30, 2026, 1:38 a.m.
NEDg Description generation batch_6a431edfab8081909213ede139801594 completed June 30, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_6a431f5f09648190821f81dfdc96588b completed June 30, 2026, 1:43 a.m.
Created at: April 10, 2026, 1:32 p.m.