Triple

T24648823
Position Surface form Disambiguated ID Type / Status
Subject Oriental region of Morocco E610190 entity
Predicate containsProvince P11085 FINISHED
Object Guercif Province
Guercif Province is an administrative division in northeastern Morocco known for its strategic location as a transport and trade crossroads between the country's interior and its eastern regions.
E1677893 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: Guercif Province | Statement: [Oriental region of Morocco, containsProvince, Guercif Province]
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: Guercif Province
Triple: [Oriental region of Morocco, containsProvince, Guercif Province]
Generated description
Guercif Province is an administrative division in northeastern Morocco known for its strategic location as a transport and trade crossroads between the country's interior and its eastern regions.

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_69e2c4d350a481909170482bc2ce6af9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40f84a8f08190913329d6d8ba4102 completed May 1, 2026, 2:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10895186348190b4865ab15bb5e1e9 completed May 22, 2026, 4:50 p.m.
NEDg Description generation batch_6a1089ee13c08190938666df6ba526e8 completed May 22, 2026, 4:53 p.m.
NED2 Entity disambiguation (via description) batch_6a108a6eeda48190a9a132ea2804d41c completed May 22, 2026, 4:55 p.m.
Created at: April 18, 2026, 2:33 a.m.