Triple

T27401680
Position Surface form Disambiguated ID Type / Status
Subject Fort Lee E691862 entity
Predicate hasGarrison P3479 FINISHED
Object U.S. Army Quartermaster Museum
The U.S. Army Quartermaster Museum is a military history museum dedicated to preserving and interpreting the heritage, artifacts, and evolving role of the U.S. Army Quartermaster Corps.
E1774027 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: U.S. Army Quartermaster Museum | Statement: [Fort Lee, hasGarrison, U.S. Army Quartermaster Museum]
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: U.S. Army Quartermaster Museum
Triple: [Fort Lee, hasGarrison, U.S. Army Quartermaster Museum]
Generated description
The U.S. Army Quartermaster Museum is a military history museum dedicated to preserving and interpreting the heritage, artifacts, and evolving role of the U.S. Army Quartermaster Corps.

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_69ef5204f7048190bf226a129858fc5b completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62cd2ceb481908cd9fae52a542206 completed May 2, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b23bc1008190bdb4e0c509e22bea completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b5c2dd1481908aba6771b5683811 completed May 24, 2026, 8:24 a.m.
NED2 Entity disambiguation (via description) batch_6a12b635ea308190b7e0d8aa242f60f1 completed May 24, 2026, 8:26 a.m.
Created at: April 27, 2026, 12:29 p.m.