Triple

T6860038
Position Surface form Disambiguated ID Type / Status
Subject Noordenveld E158251 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Roden
Roden is a town in the Dutch province of Drenthe known as a local service and population center within the municipality of Noordenveld.
 E624557 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: Roden | Statement: [Noordenveld, hasAdministrativeCenter, Roden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Roden
Context triple: [Noordenveld, hasAdministrativeCenter, Roden]
  • A. Ryen
    Ryen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local amenities, and good public transport connections.
  • B. Rennahan
    Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
  • C. Rokin
    Rokin is a major street and canal in central Amsterdam, known for its historic buildings, shops, and proximity to Dam Square.
  • D. Randolf
    Randolf is a surname most notably associated with Danish-American silent film actor Anders Randolf.
  • E. Royat
    Royat is a spa town in central France known for its thermal springs and Belle Époque architecture.
  • 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: Roden
Triple: [Noordenveld, hasAdministrativeCenter, Roden]
Generated description
Roden is a town in the Dutch province of Drenthe known as a local service and population center within the municipality of Noordenveld.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Roden
Target entity description: Roden is a town in the Dutch province of Drenthe known as a local service and population center within the municipality of Noordenveld.
  • A. Ryen
    Ryen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local amenities, and good public transport connections.
  • B. Rennahan
    Rennahan is a surname most notably associated with Ray Rennahan, an American cinematographer known for his pioneering work with Technicolor.
  • C. Rokin
    Rokin is a major street and canal in central Amsterdam, known for its historic buildings, shops, and proximity to Dam Square.
  • D. Randolf
    Randolf is a surname most notably associated with Danish-American silent film actor Anders Randolf.
  • E. Royat
    Royat is a spa town in central France known for its thermal springs and Belle Époque architecture.
  • 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_69c68830cdbc8190a8301c7a9d9f651a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8737fac81909fc546ca2bf6a278 completed March 27, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fe79af081909baacbfd4d5e8f24 completed March 28, 2026, 1:33 a.m.
NEDg Description generation batch_69c7399b95e081908bbee3a598d6513c completed March 28, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_69c739f1b20c8190a8ef57357d4956b4 completed March 28, 2026, 2:16 a.m.
Created at: March 27, 2026, 2:21 p.m.