Triple

T25258637
Position Surface form Disambiguated ID Type / Status
Subject General Reserve Engineer Force E633242 entity
Predicate branch P889 FINISHED
Object Corps of Engineers
The Corps of Engineers is a military engineering organization responsible for construction, infrastructure development, and technical support for armed forces and national projects.
E1678072 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: Corps of Engineers | Statement: [General Reserve Engineer Force, branch, Corps of Engineers]
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: Corps of Engineers
Triple: [General Reserve Engineer Force, branch, Corps of Engineers]
Generated description
The Corps of Engineers is a military engineering organization responsible for construction, infrastructure development, and technical support for armed forces and national projects.

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_69e75a922ad481908f4f1f884583cb42 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f483904578819096518f6a0a82a31f completed May 1, 2026, 10:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10896dbf908190b8d8ec0d68dedfed completed May 22, 2026, 4:50 p.m.
NEDg Description generation batch_6a108a429fd4819086b842d38c777075 completed May 22, 2026, 4:54 p.m.
NED2 Entity disambiguation (via description) batch_6a108ad0b48c8190b31b28d870e3b200 completed May 22, 2026, 4:56 p.m.
Created at: April 21, 2026, 1:13 p.m.