Triple

T2404299
Position Surface form Disambiguated ID Type / Status
Subject Eemskanaal E50239 entity
Predicate flowsNear P350 FINISHED
Object Appingedam E242557 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: Appingedam | Statement: [Eemskanaal, flowsNear, Appingedam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Appingedam
Context triple: [Eemskanaal, flowsNear, Appingedam]
  • A. Appingedam chosen
    Appingedam is a historic town and former municipality in the province of Groningen in the Netherlands, known for its medieval center and characteristic hanging kitchens over the Damsterdiep canal.
  • B. Warffum
    Warffum is a historic village in the Dutch province of Groningen, known for its traditional architecture and open-air museum showcasing rural life.
  • C. Drimmelen
    Drimmelen is a municipality and village in the southern Netherlands, known for its historic harbor and as a gateway to the Biesbosch National Park.
  • D. Beinsdorp
    Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
  • E. Borssum
    Borssum is a district of the seaport city of Emden in Lower Saxony, Germany, known primarily as a residential area with local amenities.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc8fa151081909bc6be528b29b315 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef09b92048190acfa3a85417f259c completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:58 p.m.