Triple

T8857653
Position Surface form Disambiguated ID Type / Status
Subject Landeck E210798 entity
Predicate locatedOnRiver P165 FINISHED
Object Sanna
Sanna is a river in the Tyrol region of western Austria, known as a tributary of the Inn and a popular destination for whitewater sports.
 E762648 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: Sanna | Statement: [Landeck, locatedOnRiver, Sanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sanna
Context triple: [Landeck, locatedOnRiver, Sanna]
  • A. Aino
    Aino is a tragic maiden from Finnish mythology and the national epic Kalevala, known for her ill-fated encounter with the sage Väinämöinen and her subsequent transformation into a water spirit.
  • B. Sakari
    Sakari is a Finnish given name commonly used for males, derived from the biblical name Zachary.
  • C. Neilia
    Neilia was an American educator best known as the first wife of Joe Biden, who tragically died in a car accident in 1972 along with their infant daughter.
  • D. Ylva
    Ylva is a Scandinavian female given name, traditionally associated with the meaning "she-wolf" in Old Norse.
  • E. Julanne
    Julanne is a feminine given name most notably borne by American silent film actress Julanne Johnston.
  • 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: Sanna
Triple: [Landeck, locatedOnRiver, Sanna]
Generated description
Sanna is a river in the Tyrol region of western Austria, known as a tributary of the Inn and a popular destination for whitewater sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sanna
Target entity description: Sanna is a river in the Tyrol region of western Austria, known as a tributary of the Inn and a popular destination for whitewater sports.
  • A. Aino
    Aino is a tragic maiden from Finnish mythology and the national epic Kalevala, known for her ill-fated encounter with the sage Väinämöinen and her subsequent transformation into a water spirit.
  • B. Sakari
    Sakari is a Finnish given name commonly used for males, derived from the biblical name Zachary.
  • C. Neilia
    Neilia was an American educator best known as the first wife of Joe Biden, who tragically died in a car accident in 1972 along with their infant daughter.
  • D. Ylva
    Ylva is a Scandinavian female given name, traditionally associated with the meaning "she-wolf" in Old Norse.
  • E. Julanne
    Julanne is a feminine given name most notably borne by American silent film actress Julanne Johnston.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60e3b62c8190bf779e7e1db767f6 completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0a8c0a48190b362685682e13460 completed April 3, 2026, 11:12 a.m.
NEDg Description generation batch_69cfa2658aac81909279cddab88a9fe6 completed April 3, 2026, 11:20 a.m.
NED2 Entity disambiguation (via description) batch_69cfa2f128d08190bef5011e03d64ef6 completed April 3, 2026, 11:22 a.m.
Created at: March 30, 2026, 6:50 p.m.