Triple

T25532876
Position Surface form Disambiguated ID Type / Status
Subject Bezengi Glacier E639969 entity
Predicate near P350 FINISHED
Object Mount Janga
Mount Janga is a prominent peak in the central Caucasus Mountains, known for its rugged alpine terrain and proximity to major glaciers.
E1704567 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 Janga | Statement: [Bezengi Glacier, near, Mount Janga]
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 Janga
Triple: [Bezengi Glacier, near, Mount Janga]
Generated description
Mount Janga is a prominent peak in the central Caucasus Mountains, known for its rugged alpine terrain and proximity to major glaciers.

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_69e75dbf3f9c8190b3f2a75d1b75d127 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f8647db4819098ab7374a151f6e6 completed May 2, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11074c42588190b9a93224cb11cbc0 completed May 23, 2026, 1:47 a.m.
NEDg Description generation batch_6a1109887be88190b9f86d36bf92cd03 completed May 23, 2026, 1:57 a.m.
NED2 Entity disambiguation (via description) batch_6a110a255f10819081e8d9d17a8a7cf6 completed May 23, 2026, 2 a.m.
Created at: April 21, 2026, 3:15 p.m.