Triple

T36860925
Position Surface form Disambiguated ID Type / Status
Subject Everest massif E910931 entity
Predicate hasClimbingArea P9786 FINISHED
Object Lhotse normal route
Lhotse normal route is the standard high-altitude climbing route used to ascend Lhotse, the world’s fourth-highest mountain in the Everest massif.
E2213963 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: Lhotse normal route | Statement: [Everest massif, hasClimbingArea, Lhotse normal route]
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: Lhotse normal route
Triple: [Everest massif, hasClimbingArea, Lhotse normal route]
Generated description
Lhotse normal route is the standard high-altitude climbing route used to ascend Lhotse, the world’s fourth-highest mountain in the Everest massif.

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_69f76e80f6f0819091cba8e19b269615 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cfcfe7a881908820d8db6e519442 completed May 3, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3f69f94ec08190944b30ae0343d3aa completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6b68b16c819098b8a23407c6de19 completed June 27, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6bfc11b881909dcb875cc92f5535 completed June 27, 2026, 6:21 a.m.
Created at: May 3, 2026, 4:13 p.m.