Triple

T36153274
Position Surface form Disambiguated ID Type / Status
Subject Justin Gaethje E1045650 entity
Predicate fightingOutOf P8069 FINISHED
Object Arvada, Colorado, United States
Arvada, Colorado, United States is a suburban city northwest of Denver known for its residential communities and proximity to the Denver metropolitan area.
E2172625 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: Arvada, Colorado, United States | Statement: [Justin Gaethje, fightingOutOf, Arvada, Colorado, United States]
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: Arvada, Colorado, United States
Triple: [Justin Gaethje, fightingOutOf, Arvada, Colorado, United States]
Generated description
Arvada, Colorado, United States is a suburban city northwest of Denver known for its residential communities and proximity to the Denver metropolitan area.

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_69f76e38903c8190a52887620f90aabe completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b36471f08190aaaf16a4cbf50872 completed May 3, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d4e48d481909cbc0f208dea1e05 completed June 22, 2026, 10:24 a.m.
NEDg Description generation batch_6a39111070208190ab5d19e7cf357cdc completed June 22, 2026, 10:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3911badc388190846939f78374d9ac completed June 22, 2026, 10:43 a.m.
Created at: May 3, 2026, 4:08 p.m.