Triple

T25980273
Position Surface form Disambiguated ID Type / Status
Subject King County Prosecuting Attorney E646048 entity
Predicate partOf P40 FINISHED
Object King County government
King County government is the regional governing body for King County, Washington, overseeing countywide services such as law enforcement, public health, transportation, and justice administration.
E147332 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: King County government | Statement: [King County Prosecuting Attorney, partOf, King County government]
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: King County government
Triple: [King County Prosecuting Attorney, partOf, King County government]
Generated description
King County government is the regional governing body for King County, Washington, overseeing countywide services such as law enforcement, public health, transportation, and justice administration.

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_69e77e881fc08190ba1c8dc7e2a07f97 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6050e507881909e3bc0c33e8a8c7e completed May 2, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b07991881908843e2592bf5df41 completed May 23, 2026, 3:12 a.m.
NEDg Description generation batch_6a111bd7e1188190b3275dc1efe4bfb3 completed May 23, 2026, 3:15 a.m.
NED2 Entity disambiguation (via description) batch_6a111cbb1ed88190a4980f8fc8a0a19f completed May 23, 2026, 3:19 a.m.
Created at: April 22, 2026, 8:54 a.m.