Triple

T28993701
Position Surface form Disambiguated ID Type / Status
Subject Aconcagua Region E736097 entity
Predicate hasNameOrigin P3325 FINISHED
Object Aconcagua Mountain Range
Aconcagua Mountain Range is a prominent Andean mountain system in western Argentina dominated by Mount Aconcagua, the highest peak in the Americas.
E1846550 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: Aconcagua Mountain Range | Statement: [Aconcagua Region, hasNameOrigin, Aconcagua Mountain Range]
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: Aconcagua Mountain Range
Triple: [Aconcagua Region, hasNameOrigin, Aconcagua Mountain Range]
Generated description
Aconcagua Mountain Range is a prominent Andean mountain system in western Argentina dominated by Mount Aconcagua, the highest peak in the Americas.

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_69f077eacd0481908ef0bafd74491cd0 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f65f7f067081909057e9c6e1fd0bdd completed May 2, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f5fcbd0819098f2521087d932ed completed June 7, 2026, 7:35 a.m.
NEDg Description generation batch_6a25203ca3048190b5f91e8a90cb845b completed June 7, 2026, 7:39 a.m.
NED2 Entity disambiguation (via description) batch_6a25209387fc819089c34fd92ba79bcd completed June 7, 2026, 7:41 a.m.
Created at: April 28, 2026, 9:28 a.m.