Triple

T21718462
Position Surface form Disambiguated ID Type / Status
Subject USS Maddox (DD-731) E536091 entity
Predicate namedAfter P63 FINISHED
Object William A. T. Maddox
William A. T. Maddox was a United States Marine Corps officer whose service and leadership were honored by naming the destroyer USS Maddox (DD-731) after him.
E2289903 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: William A. T. Maddox | Statement: [USS Maddox (DD-731), namedAfter, William A. T. Maddox]
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: William A. T. Maddox
Triple: [USS Maddox (DD-731), namedAfter, William A. T. Maddox]
Generated description
William A. T. Maddox was a United States Marine Corps officer whose service and leadership were honored by naming the destroyer USS Maddox (DD-731) after him.

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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efd96cc58081908dda09819041b888 completed April 27, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5b7c081aa48190bcf049be8ccdb3a8 completed July 18, 2026, 1:13 p.m.
NEDg Description generation batch_6a5b7cbe40bc8190bf241b84a77e56e2 completed July 18, 2026, 1:16 p.m.
NED2 Entity disambiguation (via description) batch_6a5b7d3b18d0819091efcf964b457b9f completed July 18, 2026, 1:18 p.m.
Created at: April 16, 2026, 6:47 p.m.