Triple

T27414819
Position Surface form Disambiguated ID Type / Status
Subject Khalaf E692861 entity
Predicate hasNotableBearer P458 FINISHED
Object Rima Khalaf
Rima Khalaf is a Jordanian economist and former United Nations official known for her leadership in Arab human development initiatives and her principled resignation from ESCWA over a report on Israeli policies.
E1772679 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: Rima Khalaf | Statement: [Khalaf, hasNotableBearer, Rima Khalaf]
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: Rima Khalaf
Triple: [Khalaf, hasNotableBearer, Rima Khalaf]
Generated description
Rima Khalaf is a Jordanian economist and former United Nations official known for her leadership in Arab human development initiatives and her principled resignation from ESCWA over a report on Israeli policies.

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_69ef5208617081908f731d312e0fd1bc completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d18f3ec8190b1e10f87305e6684 completed May 2, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b2442a0c8190bcf7cb3f00ef5e51 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b3ac2c8481908da47312d238fa0c completed May 24, 2026, 8:15 a.m.
NED2 Entity disambiguation (via description) batch_6a12b42bd380819087489bdeb2dbfab7 completed May 24, 2026, 8:17 a.m.
Created at: April 27, 2026, 12:33 p.m.