Triple

T26640133
Position Surface form Disambiguated ID Type / Status
Subject Garland County, Arkansas E668754 entity
Predicate contains P35 FINISHED
Object Garland County Courthouse
The Garland County Courthouse is the historic government building that serves as the judicial and administrative center for Garland County in Arkansas.
E1736459 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: Garland County Courthouse | Statement: [Garland County, Arkansas, contains, Garland County Courthouse]
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: Garland County Courthouse
Triple: [Garland County, Arkansas, contains, Garland County Courthouse]
Generated description
The Garland County Courthouse is the historic government building that serves as the judicial and administrative center for Garland County in Arkansas.

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_69ee9d0024b8819090a7c8cf669a3b6c completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f616313e788190b2d72b07960f4466 completed May 2, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec3f176c819093139c14525c7df5 completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11f74329f48190a78ce3f209f8a134 completed May 23, 2026, 6:51 p.m.
NED2 Entity disambiguation (via description) batch_6a11f7d911448190ae1b41d1cff8a85e completed May 23, 2026, 6:54 p.m.
Created at: April 27, 2026, 2:29 a.m.