Triple

T3561781
Position Surface form Disambiguated ID Type / Status
Subject Sde Dov Airport E75353 entity
Predicate hasCivilSection P50378 FINISHED
Object domestic passenger terminal 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: domestic passenger terminal | Statement: [Sde Dov Airport, hasCivilSection, domestic passenger terminal]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCivilSection
Context triple: [Sde Dov Airport, hasCivilSection, domestic passenger terminal]
  • A. hasCivilDivision
    Indicates that one administrative or political entity is subdivided into, or is associated with, a specific civil division (such as a county, district, or municipality).
  • B. hasSect
    Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
  • C. hasMunicipalSections
    Indicates that a municipality is divided into and associated with specific internal administrative sections or districts.
  • D. hasSectionOn
    Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
  • E. hasSectionIn
    Indicates that one entity contains or includes another entity as a section or subdivision within it.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc08bdde88190915d2f6ddf26e00e completed March 8, 2026, 6:31 p.m.
PD Predicate disambiguation batch_69adb834779081908468e182d5f6cf02 completed March 8, 2026, 5:56 p.m.
PDg Predicate description generation batch_69adb9bbb62c8190989629ca11733e1b completed March 8, 2026, 6:02 p.m.
Created at: March 8, 2026, 3:21 p.m.