Triple

T26598702
Position Surface form Disambiguated ID Type / Status
Subject Minnesota National Guard E667563 entity
Predicate hasComponent P35 FINISHED
Object Minnesota Army National Guard
The Minnesota Army National Guard is the land-based military reserve force of the state of Minnesota, providing trained units to support both state emergencies and federal missions.
E667563 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: Minnesota Army National Guard | Statement: [Minnesota National Guard, hasComponent, Minnesota Army National Guard]
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: Minnesota Army National Guard
Triple: [Minnesota National Guard, hasComponent, Minnesota Army National Guard]
Generated description
The Minnesota Army National Guard is the land-based military reserve force of the state of Minnesota, providing trained units to support both state emergencies and federal missions.

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_69ee9cfc385081909ac9ae178030a06e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f6156db8c081909facff45ff1cda55 completed May 2, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c83f3f288190aed2546950bc946e completed May 23, 2026, 3:31 p.m.
NEDg Description generation batch_6a11c91aa6888190b17f656a39eefd1e completed May 23, 2026, 3:34 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca6f162c8190a8c7fbc1e188ea90 completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 2:11 a.m.