Triple

T20137935
Position Surface form Disambiguated ID Type / Status
Subject Viimsi Peninsula E491073 entity
Predicate containsSettlement P847 FINISHED
Object Haabneeme NE NERFINISHED

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: Haabneeme | Statement: [Viimsi Peninsula, containsSettlement, Haabneeme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haabneeme
Context triple: [Viimsi Peninsula, containsSettlement, Haabneeme]
  • A. Haabneeme chosen
    Haabneeme is a small coastal settlement in northern Estonia, located on the Viimsi Peninsula near Tallinn.
  • B. Herbaijum
    Herbaijum is a small village in the province of Friesland in the Netherlands.
  • C. Mahmee
    Mahmee is a maternal and infant healthcare startup that provides technology-enabled care coordination and support for new and expecting parents.
  • D. Hamul
    Hamul is a minor biblical figure listed in the Book of Genesis as one of the descendants of Judah and a member of the early Israelite family lineage.
  • E. Hannut
    Hannut is a municipality in the French-speaking Walloon Region of Belgium, known for its rural character and location between Liège and Brussels.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676879f48190a59da04393d2a8cc completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:32 p.m.