Triple

T24348742
Position Surface form Disambiguated ID Type / Status
Subject Ayt Seghrouchen dialect E613722 entity
Predicate region P40 FINISHED
Object Middle Atlas area of Morocco
The Middle Atlas area of Morocco is a mountainous region in central Morocco known for its Berber (Amazigh) communities, cedar forests, and distinct local dialects and cultures.
E1459243 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: Middle Atlas area of Morocco | Statement: [Ayt Seghrouchen dialect, region, Middle Atlas area of Morocco]
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: Middle Atlas area of Morocco
Triple: [Ayt Seghrouchen dialect, region, Middle Atlas area of Morocco]
Generated description
The Middle Atlas area of Morocco is a mountainous region in central Morocco known for its Berber (Amazigh) communities, cedar forests, and distinct local dialects and cultures.

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_69e2d7ddd29481909e7f539a6072bd71 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f293430524819087984a699d1d3687 completed April 29, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd665569c819086969570f28cf944 completed May 22, 2026, 4:07 a.m.
NEDg Description generation batch_6a0fd726b1b08190a13ac712e0d40a7a completed May 22, 2026, 4:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd852ca8c81909bf1731a342d4a6d completed May 22, 2026, 4:15 a.m.
Created at: April 18, 2026, 1:58 a.m.