Triple

T16688205
Position Surface form Disambiguated ID Type / Status
Subject Friesland district E405521 entity
Predicate contains P35 FINISHED
Object Varel
Varel is a coastal town in northwestern Germany known for its location near the Jade Bight and its mix of maritime industry and tourism.
 E1228409 NE FINISHED

How this triple was built (4 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: Varel | Statement: [Friesland district, contains, Varel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Varel
Context triple: [Friesland district, contains, Varel]
  • A. Varín
    Varín is a village and municipality in northern Slovakia, situated near the Malá Fatra mountain range and serving as a gateway to the surrounding national park.
  • B. Värska
    Värska is a village in southeastern Estonia known as a cultural center of the Seto people and for its traditional Seto heritage and mineral water.
  • C. Vaas
    Vaas is a Sri Lankan surname most famously associated with Chaminda Vaas, a former international cricketer and one of Sri Lanka’s greatest fast bowlers.
  • D. Varbelvitz
    Varbelvitz is a small rural village located on the island municipality of Ummanz in Mecklenburg-Vorpommern, northern Germany.
  • E. Vonderort
    Vonderort is a district of the city of Bottrop in North Rhine-Westphalia, Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Varel
Triple: [Friesland district, contains, Varel]
Generated description
Varel is a coastal town in northwestern Germany known for its location near the Jade Bight and its mix of maritime industry and tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Varel
Target entity description: Varel is a coastal town in northwestern Germany known for its location near the Jade Bight and its mix of maritime industry and tourism.
  • A. Varín
    Varín is a village and municipality in northern Slovakia, situated near the Malá Fatra mountain range and serving as a gateway to the surrounding national park.
  • B. Värska
    Värska is a village in southeastern Estonia known as a cultural center of the Seto people and for its traditional Seto heritage and mineral water.
  • C. Vaas
    Vaas is a Sri Lankan surname most famously associated with Chaminda Vaas, a former international cricketer and one of Sri Lanka’s greatest fast bowlers.
  • D. Varbelvitz
    Varbelvitz is a small rural village located on the island municipality of Ummanz in Mecklenburg-Vorpommern, northern Germany.
  • E. Vonderort
    Vonderort is a district of the city of Bottrop in North Rhine-Westphalia, Germany.
  • F. None of above. chosen

Provenance (5 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea75df481909a7ebb9b2a9d0afd completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a45af7c8190bfe09dd0e0573573 completed May 10, 2026, 1:38 p.m.
NEDg Description generation batch_6a008b41a1648190bd1c2268c8a80ee2 completed May 10, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_6a008c2bcac48190801ba34fde104a8a completed May 10, 2026, 1:46 p.m.
Created at: April 10, 2026, 5:19 a.m.