Triple

T3415990
Position Surface form Disambiguated ID Type / Status
Subject Mijnsheerenland E72008 entity
Predicate hasOfficialName P66 FINISHED
Object Mijnsheerenland E72008 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: Mijnsheerenland | Statement: [Mijnsheerenland, hasOfficialName, Mijnsheerenland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mijnsheerenland
Context triple: [Mijnsheerenland, hasOfficialName, Mijnsheerenland]
  • A. Mijnsheerenland chosen
    Mijnsheerenland is a village in the Dutch province of South Holland, known for its rural character and location on the island of Hoeksche Waard.
  • B. Vijfheerenlanden
    Vijfheerenlanden is a historical region in the Netherlands known for its polder landscape and long-standing water management traditions along the Lek River.
  • C. Ommelanden
    Ommelanden is the rural region surrounding the city of Groningen in the northern Netherlands, historically known for its Frisian culture and agricultural landscape.
  • D. Landsmeer
    Landsmeer is a small Dutch town and municipality in North Holland, situated just north of Amsterdam and known for its watery landscapes and nature reserves.
  • E. Rietlanden
    Rietlanden is a waterfront area in Amsterdam’s Eastern Docklands, known for its former industrial port functions and subsequent urban redevelopment.
  • 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb92ae6148190958d6bb735258cab completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34be316a88190a15cb1e9f31b57d0 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.