Triple

T29584490
Position Surface form Disambiguated ID Type / Status
Subject Director-General of the United Nations Office at Nairobi E753683 entity
Predicate oneOfFourMainOffices P17491 FINISHED
Object United Nations Office at Nairobi NE NERFINISHED

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: United Nations Office at Nairobi | Statement: [Director-General of the United Nations Office at Nairobi, oneOfFourMainOffices, United Nations Office at Nairobi]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: oneOfFourMainOffices
Context triple: [Director-General of the United Nations Office at Nairobi, oneOfFourMainOffices, United Nations Office at Nairobi]
  • A. mainOffice
    Indicates that one location or office serves as the primary or central office for an organization or entity.
  • B. hasNumberOfRegionalOffices
    Indicates the quantity of regional offices that an entity possesses or operates.
  • C. numberOfOffices
    Indicates the total count of offices associated with a given entity.
  • D. oneOfFourMainUNOffices chosen
    Indicates that an entity is one of the four principal main offices of the United Nations.
  • E. headquartersOfOffice
    Indicates that a particular location serves as the main headquarters for a specified office or organizational unit.
  • F. None of above.

Provenance (3 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_69f0ef80bf8c8190ad286e99f7df0c63 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f676f968d08190a4adba0439b438c9 completed May 2, 2026, 10:13 p.m.
PD Predicate disambiguation batch_69f675ff62c48190a634bbb8896973b9 completed May 2, 2026, 10:09 p.m.
Created at: April 28, 2026, 6:09 p.m.