Triple

T3682541
Position Surface form Disambiguated ID Type / Status
Subject Stockholm tramways E78142 entity
Predicate connects P390 FINISHED
Object Alvik
Alvik is a district in western Stockholm known as a key public transport hub, particularly for its tram and metro connections.
 E379961 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: Alvik | Statement: [Stockholm tramways, connects, Alvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alvik
Context triple: [Stockholm tramways, connects, Alvik]
  • A. Larsmo
    Larsmo is a coastal municipality in western Finland known for its archipelago and Swedish-speaking majority population.
  • B. Arve
    The Arve is a river in southwestern Switzerland and southeastern France that flows through Geneva before joining the Rhône.
  • C. Avsola
    Avsola is a biosimilar monoclonal antibody to infliximab used to treat various autoimmune inflammatory conditions.
  • D. Givors
    Givors is a commune in eastern France located in the Metropolis of Lyon, known historically as an industrial and river-port town on the Rhône.
  • E. Alaior
    Alaior is a historic inland town and municipality on the Spanish island of Menorca, known for its traditional architecture and local cheese production.
  • 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: Alvik
Triple: [Stockholm tramways, connects, Alvik]
Generated description
Alvik is a district in western Stockholm known as a key public transport hub, particularly for its tram and metro connections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alvik
Target entity description: Alvik is a district in western Stockholm known as a key public transport hub, particularly for its tram and metro connections.
  • A. Larsmo
    Larsmo is a coastal municipality in western Finland known for its archipelago and Swedish-speaking majority population.
  • B. Arve
    The Arve is a river in southwestern Switzerland and southeastern France that flows through Geneva before joining the Rhône.
  • C. Avsola
    Avsola is a biosimilar monoclonal antibody to infliximab used to treat various autoimmune inflammatory conditions.
  • D. Givors
    Givors is a commune in eastern France located in the Metropolis of Lyon, known historically as an industrial and river-port town on the Rhône.
  • E. Alaior
    Alaior is a historic inland town and municipality on the Spanish island of Menorca, known for its traditional architecture and local cheese production.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4948cc48190ab1f59cc4a2437cc completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3b306c081909b3857daa4f97ce2 completed March 14, 2026, 2:10 a.m.
NEDg Description generation batch_69b4c56b76ac81909ae8d2ef10b8ed28 completed March 14, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69b4c62f7b7c81909150d8e40bb2dda4 completed March 14, 2026, 2:21 a.m.
Created at: March 8, 2026, 3:25 p.m.