Triple

T32137091
Position Surface form Disambiguated ID Type / Status
Subject Mount Muir E820796 entity
Predicate firstAscentBy P1321 FINISHED
Object LeRoy Jeffers
LeRoy Jeffers was an early 20th-century American mountaineer and explorer known for pioneering ascents in the Sierra Nevada.
E1999707 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: LeRoy Jeffers | Statement: [Mount Muir, firstAscentBy, LeRoy Jeffers]
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: LeRoy Jeffers
Triple: [Mount Muir, firstAscentBy, LeRoy Jeffers]
Generated description
LeRoy Jeffers was an early 20th-century American mountaineer and explorer known for pioneering ascents in the Sierra Nevada.

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_69f349039e0c819091c7a7d322e3f46d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b9aa7bb4819082571b42370dcd4a completed May 3, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46bd1890819089799969a2a94e03 completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f65f6542c8190bd54a1bf64317371 completed June 15, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_6a2f66670a1081909e6baa6e4cd8cc71 completed June 15, 2026, 2:41 a.m.
Created at: May 1, 2026, 12:30 a.m.