Triple

T27080955
Position Surface form Disambiguated ID Type / Status
Subject Lorillard family E685593 entity
Predicate hasNotableMember P304 FINISHED
Object Pierre Lorillard III
Pierre Lorillard III was a prominent 19th-century American tobacco magnate and socialite, known for expanding his family’s tobacco business and helping develop the Tuxedo Park resort community in New York.
 E1759598 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: Pierre Lorillard III | Statement: [Lorillard family, hasNotableMember, Pierre Lorillard III]
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: Pierre Lorillard III
Triple: [Lorillard family, hasNotableMember, Pierre Lorillard III]
Generated description
Pierre Lorillard III was a prominent 19th-century American tobacco magnate and socialite, known for expanding his family’s tobacco business and helping develop the Tuxedo Park resort community in New York.

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_69ef14843b1481909d828b3d5a44550a completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62318edf8819086df745876d12eac completed May 2, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12536f7bbc8190b25a5b8eda928b66 completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a125433c0288190ab1e54c3d763468d completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a1254f46d288190aa6f45f8c8e9007d completed May 24, 2026, 1:31 a.m.
Created at: April 27, 2026, 8:34 a.m.