Triple

T18603531
Position Surface form Disambiguated ID Type / Status
Subject Nishi Ward Office E454677 entity
Predicate administrativeDivisionTypeServed P106792 FINISHED
Object ward 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: ward | Statement: [Nishi Ward Office, administrativeDivisionTypeServed, ward]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: administrativeDivisionTypeServed
Context triple: [Nishi Ward Office, administrativeDivisionTypeServed, ward]
  • A. appliesToAdministrativeDivisionType chosen
    Indicates that something is relevant or applicable specifically to a certain type or category of administrative division.
  • B. countrySubdivisionServed
    Indicates a relationship where a service, organization, or entity operates within and provides its offerings to a specific administrative region or subdivision of a country.
  • C. usesAdministrativeDivisionType
    Indicates that one entity employs or applies a particular type of administrative division as part of its territorial or organizational structure.
  • D. areaServedType
    Indicates the type or category of area that is served by an entity or service.
  • E. administrativeTerritoryType
    Indicates the classification of an administrative area according to its level or type of territorial governance (e.g., city, county, province).
  • 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54752abec8190a5f4aa84abe8b240 completed April 19, 2026, 9:21 p.m.
PD Predicate disambiguation batch_69e478cf5e888190a0b1074b0c6525df completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 11:45 a.m.