Triple

T25590989
Position Surface form Disambiguated ID Type / Status
Subject Mendenhall Valley E641521 entity
Predicate hasNearbyMountain P651 FINISHED
Object Thunder Mountain
Thunder Mountain is a prominent peak near Juneau, Alaska, known for its scenic views over the Mendenhall Valley and the nearby Mendenhall Glacier.
E1773271 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: Thunder Mountain | Statement: [Mendenhall Valley, hasNearbyMountain, Thunder Mountain]
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: Thunder Mountain
Triple: [Mendenhall Valley, hasNearbyMountain, Thunder Mountain]
Generated description
Thunder Mountain is a prominent peak near Juneau, Alaska, known for its scenic views over the Mendenhall Valley and the nearby Mendenhall Glacier.

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_69e75dc60d108190b7e2419e36b0134b completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f96cc064819088071450af183d1c completed May 2, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b20f13008190b85126166601c110 completed May 24, 2026, 8:08 a.m.
NEDg Description generation batch_6a12b379225c8190aca2d280575a3f7a completed May 24, 2026, 8:14 a.m.
NED2 Entity disambiguation (via description) batch_6a12b44191688190899b55266e559ede completed May 24, 2026, 8:18 a.m.
Created at: April 21, 2026, 4:24 p.m.