Triple

T36119621
Position Surface form Disambiguated ID Type / Status
Subject Government Council of Morocco E1044707 entity
Predicate reportsTo P258 FINISHED
Object King of Morocco
The King of Morocco is the hereditary monarch and head of state who holds significant political, religious, and military authority within the Kingdom of Morocco.
E257123 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: King of Morocco | Statement: [Government Council of Morocco, reportsTo, King 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: King of Morocco
Triple: [Government Council of Morocco, reportsTo, King of Morocco]
Generated description
The King of Morocco is the hereditary monarch and head of state who holds significant political, religious, and military authority within the Kingdom of Morocco.

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_69f76e356c908190abc6ca1e6a05b011 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b2cebe088190a9f85263549d81fb completed May 3, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38de0ac8d88190b7b3a0819b25287e completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38f194b6f881909e27fe73c83c2b1d completed June 22, 2026, 8:25 a.m.
NED2 Entity disambiguation (via description) batch_6a38f35df5308190991210dda64a0083 completed June 22, 2026, 8:33 a.m.
Created at: May 3, 2026, 4:08 p.m.