Triple

T25136232
Position Surface form Disambiguated ID Type / Status
Subject Kamnik Saddle E629664 entity
Predicate isAccessPointFor P26211 FINISHED
Object Mount Planjava
Mount Planjava is a prominent peak in Slovenia’s Kamnik–Savinja Alps, known for its steep limestone walls, panoramic views, and popularity among experienced hikers and climbers.
E1690977 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: Mount Planjava | Statement: [Kamnik Saddle, isAccessPointFor, Mount Planjava]
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: Mount Planjava
Triple: [Kamnik Saddle, isAccessPointFor, Mount Planjava]
Generated description
Mount Planjava is a prominent peak in Slovenia’s Kamnik–Savinja Alps, known for its steep limestone walls, panoramic views, and popularity among experienced hikers and climbers.

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_69e2ff338250819096ff6c8892804389 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f465ff8c1881909f42c293b0da9804 completed May 1, 2026, 8:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c1111acc819090a5ad9701f5ac12 completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c22b19a48190b04130bdb7763f0a completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2de07648190858ba8901748aa53 completed May 22, 2026, 8:55 p.m.
Created at: April 18, 2026, 6:29 a.m.