Triple

T27770085
Position Surface form Disambiguated ID Type / Status
Subject Sheikha Fatima bint Mubarak Al Ketbi E701719 entity
Predicate associatedWith P37 FINISHED
Object General Women's Union
The General Women's Union is a leading Emirati organization dedicated to advancing women's rights, empowerment, and social development in the United Arab Emirates.
E1788035 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: General Women's Union | Statement: [Sheikha Fatima bint Mubarak Al Ketbi, associatedWith, General Women's Union]
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: General Women's Union
Triple: [Sheikha Fatima bint Mubarak Al Ketbi, associatedWith, General Women's Union]
Generated description
The General Women's Union is a leading Emirati organization dedicated to advancing women's rights, empowerment, and social development in the United Arab Emirates.

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_69ef6a52fa708190934a32308d2c92dc completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f637962be88190b63239f6e4b782f4 completed May 2, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecb9030881909e78ab07fc8505a3 completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ed2afa9481909cc0ca56270ba2a0 completed May 24, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a12edccfe54819094da363072bdf7a6 completed May 24, 2026, 12:23 p.m.
Created at: April 27, 2026, 4:34 p.m.