Triple

T10393981
Position Surface form Disambiguated ID Type / Status
Subject Kristina från Duvemåla E244959 entity
Predicate hasMusicalNumber P20452 FINISHED
Object Stanna
"Stanna" is a musical number from the Swedish musical "Kristina från Duvemåla," known for its emotional depth and reflection on longing and belonging.
E859338 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: Stanna | Statement: [Kristina från Duvemåla, hasMusicalNumber, Stanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stanna
Context triple: [Kristina från Duvemåla, hasMusicalNumber, Stanna]
  • A. Strendur
    Strendur is a village and important local settlement on the island of Eysturoy in the Faroe Islands.
  • B. Thamserku
    Thamserku is a prominent Himalayan peak in eastern Nepal, known for its steep, dramatic profile and popularity among experienced mountaineers.
  • C. Störnstein
    Störnstein is a small municipality in the Upper Palatinate region of Bavaria, Germany.
  • D. Sinnuris
    Sinnuris is a town and administrative center located in Egypt’s Faiyum Governorate, known for its agricultural surroundings and proximity to Lake Qarun.
  • E. Urstein
    Urstein is a locality in the municipality of Puch bei Hallein in the Austrian state of Salzburg, known for hosting the Salzburg University of Applied Sciences campus.
  • 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: Stanna
Triple: [Kristina från Duvemåla, hasMusicalNumber, Stanna]
Generated description
"Stanna" is a musical number from the Swedish musical "Kristina från Duvemåla," known for its emotional depth and reflection on longing and belonging.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stanna
Target entity description: "Stanna" is a musical number from the Swedish musical "Kristina från Duvemåla," known for its emotional depth and reflection on longing and belonging.
  • A. Strendur
    Strendur is a village and important local settlement on the island of Eysturoy in the Faroe Islands.
  • B. Thamserku
    Thamserku is a prominent Himalayan peak in eastern Nepal, known for its steep, dramatic profile and popularity among experienced mountaineers.
  • C. Störnstein
    Störnstein is a small municipality in the Upper Palatinate region of Bavaria, Germany.
  • D. Sinnuris
    Sinnuris is a town and administrative center located in Egypt’s Faiyum Governorate, known for its agricultural surroundings and proximity to Lake Qarun.
  • E. Urstein
    Urstein is a locality in the municipality of Puch bei Hallein in the Austrian state of Salzburg, known for hosting the Salzburg University of Applied Sciences campus.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b795fc8190aa50ce3c7360ff83 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d795c8271c81908a6b67822050c06d completed April 9, 2026, 12:04 p.m.
NEDg Description generation batch_69d7975191ac8190b32eb6cc1f5c88aa completed April 9, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d798655c7c8190a5da5ef976102285 completed April 9, 2026, 12:15 p.m.
Created at: April 6, 2026, 12:06 p.m.