Triple

T16820061
Position Surface form Disambiguated ID Type / Status
Subject Burgazada E408862 entity
Predicate partOf P40 FINISHED
Object Adalar municipality E639213 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: Adalar municipality | Statement: [Burgazada, partOf, Adalar municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adalar municipality
Context triple: [Burgazada, partOf, Adalar municipality]
  • A. Adalar Municipality chosen
    Adalar Municipality is the local government authority responsible for administering public services and urban management on Istanbul’s Princes’ Islands district.
  • B. Dili municipality
    Dili municipality is an administrative region in East Timor that encompasses the national capital, Dili, and serves as the country’s political and economic center.
  • C. Symi municipality
    Symi municipality is the local administrative authority governing the Greek island of Symi in the Dodecanese, known for its neoclassical harbor town and maritime heritage.
  • D. Nora Municipality
    Nora Municipality is a local government area in central Sweden known for its historic wooden town of Nora and surrounding lakes and forests.
  • E. Bardu Municipality
    Bardu Municipality is a sparsely populated inland municipality in Troms og Finnmark county, Norway, known for its military presence, forests, and mountainous wilderness.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e56b9c8190a35ad9c463954fbf completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b29a3854819099eed580eea5d84d completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.