Triple

T23461897
Position Surface form Disambiguated ID Type / Status
Subject Kanab Visitor Center E569000 entity
Predicate county P75 FINISHED
Object Kane County
Kane County is a rural county in southern Utah known for its striking desert landscapes, slot canyons, and proximity to national parks such as Zion, Bryce Canyon, and the Grand Canyon’s North Rim.
E1697820 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: Kane County | Statement: [Kanab Visitor Center, county, Kane County]
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: Kane County
Triple: [Kanab Visitor Center, county, Kane County]
Generated description
Kane County is a rural county in southern Utah known for its striking desert landscapes, slot canyons, and proximity to national parks such as Zion, Bryce Canyon, and the Grand Canyon’s North Rim.

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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a69bc200819096ed2baf25cdee4f completed April 29, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9d054248190ba78bbefd1342268 completed May 22, 2026, 10:33 p.m.
NEDg Description generation batch_6a10db772c408190875e23a357eb75d9 completed May 22, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_6a10dc2096b881909e87c9cc277bc831 completed May 22, 2026, 10:43 p.m.
Created at: April 17, 2026, 5:54 p.m.