Triple

T35189050
Position Surface form Disambiguated ID Type / Status
Subject Preble’s Boys E1016067 entity
Predicate hasMember P10 FINISHED
Object Benjamin H. Porter
Benjamin H. Porter was a United States Navy officer known for his service under Commodore Edward Preble during the early 19th century, particularly in the First Barbary War.
E2291107 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: Benjamin H. Porter | Statement: [Preble’s Boys, hasMember, Benjamin H. Porter]
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: Benjamin H. Porter
Triple: [Preble’s Boys, hasMember, Benjamin H. Porter]
Generated description
Benjamin H. Porter was a United States Navy officer known for his service under Commodore Edward Preble during the early 19th century, particularly in the First Barbary War.

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_69f76ddd815c8190b822eea06630f9fb completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78dc57dac81908b5aa4957ca02bd2 completed May 3, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c25a87ffc8190828493bdee06890f completed July 19, 2026, 1:17 a.m.
NEDg Description generation batch_6a5c26d6c7d48190a16c765b56176156 completed July 19, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a5c2b09bd648190816ea37cf33623d5 completed July 19, 2026, 1:40 a.m.
Created at: May 3, 2026, 4:02 p.m.