Triple

T27209752
Position Surface form Disambiguated ID Type / Status
Subject Gutzon Borglum E683965 entity
Predicate sibling P363 FINISHED
Object Solon Borglum
Solon Borglum was an American sculptor renowned for his depictions of frontier life and Western themes in bronze and stone.
E1771691 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: Solon Borglum | Statement: [Gutzon Borglum, sibling, Solon Borglum]
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: Solon Borglum
Triple: [Gutzon Borglum, sibling, Solon Borglum]
Generated description
Solon Borglum was an American sculptor renowned for his depictions of frontier life and Western themes in bronze and stone.

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_69eefad339a08190aeacb2a198f1a39b completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625e8342c8190a809bfb169967a89 completed May 2, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b224afcc8190a1c95f1261073122 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b32353248190ac509d73a9910602 completed May 24, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a12b3c695a0819099113dba54710362 completed May 24, 2026, 8:16 a.m.
Created at: April 27, 2026, 9:39 a.m.