Triple

T5371380
Position Surface form Disambiguated ID Type / Status
Subject North Hesse E108856 entity
Predicate traversedByRiver P165 FINISHED
Object Eder
The Eder is a river in central Germany that flows through the state of Hesse before joining the Fulda River.
 E516244 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: Eder | Statement: [North Hesse, traversedByRiver, Eder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Eder
Context triple: [North Hesse, traversedByRiver, Eder]
  • A. Éder
    Éder is a Portuguese footballer best known for scoring the extra-time winning goal that secured Portugal’s first major international trophy at UEFA Euro 2016.
  • B. Estévez
    Estévez is the original Spanish family name of actor Martin Sheen, also shared by several of his children in the entertainment industry.
  • C. Álvaro
    Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
  • D. Llorente
    Llorente is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and access to the Pacific Ocean.
  • E. Renaldo
    Renaldo is the titular character in Bob Dylan’s 1978 film "Renaldo and Clara," a surreal, semi-autobiographical drama blending concert footage with fictional vignettes.
  • 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: Eder
Triple: [North Hesse, traversedByRiver, Eder]
Generated description
The Eder is a river in central Germany that flows through the state of Hesse before joining the Fulda River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Eder
Target entity description: The Eder is a river in central Germany that flows through the state of Hesse before joining the Fulda River.
  • A. Éder
    Éder is a Portuguese footballer best known for scoring the extra-time winning goal that secured Portugal’s first major international trophy at UEFA Euro 2016.
  • B. Estévez
    Estévez is the original Spanish family name of actor Martin Sheen, also shared by several of his children in the entertainment industry.
  • C. Álvaro
    Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
  • D. Llorente
    Llorente is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and access to the Pacific Ocean.
  • E. Renaldo
    Renaldo is the titular character in Bob Dylan’s 1978 film "Renaldo and Clara," a surreal, semi-autobiographical drama blending concert footage with fictional vignettes.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86aa0f5c8190ba96554e75696f8e completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf29347a18819083115fe68db8e708 completed March 21, 2026, 11:26 p.m.
NEDg Description generation batch_69bf2a23ba1881909ddc549728bbc2d3 completed March 21, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_69bf2e6d5f9081908327dff0058241f0 completed March 21, 2026, 11:49 p.m.
Created at: March 20, 2026, 2:02 p.m.