Triple

T36097261
Position Surface form Disambiguated ID Type / Status
Subject Louisville, Colorado E1044096 entity
Predicate hasEvent P811 FINISHED
Object Louisville Street Faire
The Louisville Street Faire is a popular seasonal community festival in downtown Louisville, Colorado, featuring live music, food vendors, and family-friendly activities.
E2168389 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: Louisville Street Faire | Statement: [Louisville, Colorado, hasEvent, Louisville Street Faire]
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: Louisville Street Faire
Triple: [Louisville, Colorado, hasEvent, Louisville Street Faire]
Generated description
The Louisville Street Faire is a popular seasonal community festival in downtown Louisville, Colorado, featuring live music, food vendors, and family-friendly activities.

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_69f76e32d60c8190ba781ffaaab4aa3d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b26c837c8190bea94735e30ad64d completed May 3, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38d54aab248190a865e10399e92f5a completed June 22, 2026, 6:25 a.m.
NEDg Description generation batch_6a38d5e83b58819080bd6a95a17f6b2b completed June 22, 2026, 6:27 a.m.
NED2 Entity disambiguation (via description) batch_6a38d681cf388190896a30e2b0939181 completed June 22, 2026, 6:30 a.m.
Created at: May 3, 2026, 4:08 p.m.