Triple

T26082585
Position Surface form Disambiguated ID Type / Status
Subject Queen Farida of Egypt E657884 entity
Predicate title P38 FINISHED
Object Her Majesty The Queen of Egypt
Her Majesty The Queen of Egypt is the royal style held by Queen Farida, the first wife of King Farouk and a prominent queen consort of modern Egypt.
E1706809 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: Her Majesty The Queen of Egypt | Statement: [Queen Farida of Egypt, title, Her Majesty The Queen of Egypt]
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: Her Majesty The Queen of Egypt
Triple: [Queen Farida of Egypt, title, Her Majesty The Queen of Egypt]
Generated description
Her Majesty The Queen of Egypt is the royal style held by Queen Farida, the first wife of King Farouk and a prominent queen consort of modern Egypt.

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_69ee5bbf0d208190801ee95d4f07fb16 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f606fcb3c48190930c7c6e532524d1 completed May 2, 2026, 2:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b360350819086df0e103fb680c1 completed May 23, 2026, 3:12 a.m.
NEDg Description generation batch_6a111c964b408190bb5820d6f197ca09 completed May 23, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a111d127a988190876a162a3a44540c completed May 23, 2026, 3:20 a.m.
Created at: April 26, 2026, 7:39 p.m.