Triple

T8640316
Position Surface form Disambiguated ID Type / Status
Subject State House Road, Nairobi E204627 entity
Predicate hasNearbyInstitutionType P84383 FINISHED
Object executive branch of government LITERAL 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: executive branch of government | Statement: [State House Road, Nairobi, hasNearbyInstitutionType, executive branch of government]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNearbyInstitutionType
Context triple: [State House Road, Nairobi, hasNearbyInstitutionType, executive branch of government]
  • A. hasNearbyInstitution
    Indicates that one entity is located close to or in the immediate vicinity of an institution.
  • B. campusProximity
    Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
  • C. hasLocalInstitution
    Indicates that a given place or region possesses or hosts an institution that operates locally within its boundaries.
  • D. adjacentToCampusOf
    Indicates that one entity is located next to or directly bordering the campus area of another entity.
  • E. hasNearbyFacility
    Indicates that one entity is located close to or in the vicinity of a particular facility.
  • F. None of above. chosen

Provenance (4 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_69ca834ca1c88190a11ffb0200342fac completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc47944d1c819081f448f14d04bf9d completed March 31, 2026, 10:15 p.m.
PD Predicate disambiguation batch_69cc455d6d448190a2da2a319ac78c37 completed March 31, 2026, 10:06 p.m.
PDg Predicate description generation batch_69cc479284a8819099b0b0d879af3372 completed March 31, 2026, 10:15 p.m.
Created at: March 30, 2026, 6:28 p.m.