Triple

T5270873
Position Surface form Disambiguated ID Type / Status
Subject Kolding E119252 entity
Predicate hasNearbyBodyOfWater P8567 FINISHED
Object Little Belt E179745 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: Little Belt | Statement: [Kolding, hasNearbyBodyOfWater, Little Belt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Little Belt
Context triple: [Kolding, hasNearbyBodyOfWater, Little Belt]
  • A. Little Belt chosen
    Little Belt is a narrow strait in Denmark that separates the island of Funen from the Jutland Peninsula and connects the Baltic Sea with the Kattegat.
  • B. Lochnagar
    Lochnagar is a prominent mountain in the Cairngorms of Scotland, famed for its dramatic north-facing corrie and connections to royal Deeside.
  • C. Port Tennant
    Port Tennant is a residential and industrial district of Swansea in South Wales, situated near the city’s docks and eastern waterfront.
  • D. Schley
    Schley is a surname of German origin borne by various notable individuals, including American politicians and military figures.
  • E. The Helena
    The Helena is a prominent eco-friendly luxury residential skyscraper in Manhattan, New York City, developed by The Durst Organization.
  • 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_69bd446c38e081908cdaf113bdf86790 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7c1fa01081909d589686289b624b completed March 20, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe9691608190bae0865f80e23062 completed March 21, 2026, 8:24 p.m.
Created at: March 20, 2026, 1:51 p.m.