Triple

T13798460
Position Surface form Disambiguated ID Type / Status
Subject Stange municipality E331576 entity
Predicate hasSettlement P1068 FINISHED
Object Tangen
Tangen is a village in Stange municipality in Innlandet county, Norway, known for its residential character and proximity to the lake Mjøsa.
E1061043 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: Tangen | Statement: [Stange municipality, hasSettlement, Tangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tangen
Context triple: [Stange municipality, hasSettlement, Tangen]
  • A. Tangen
    Tangen is a former settlement in Norway that was incorporated into the city of Drammen through a municipal merger.
  • B. Tunasan
    Tunasan is a barangay and district in the southern part of Muntinlupa City in Metro Manila, Philippines.
  • C. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • D. Letang
    Letang is the surname of Kris Letang, a professional ice hockey defenseman best known for his long career with the NHL’s Pittsburgh Penguins.
  • E. Tangale
    Tangale is a West Chadic language spoken primarily in Gombe State, northeastern Nigeria, by the Tangale people.
  • 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: Tangen
Triple: [Stange municipality, hasSettlement, Tangen]
Generated description
Tangen is a village in Stange municipality in Innlandet county, Norway, known for its residential character and proximity to the lake Mjøsa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tangen
Target entity description: Tangen is a village in Stange municipality in Innlandet county, Norway, known for its residential character and proximity to the lake Mjøsa.
  • A. Tangen
    Tangen is a former settlement in Norway that was incorporated into the city of Drammen through a municipal merger.
  • B. Tunasan
    Tunasan is a barangay and district in the southern part of Muntinlupa City in Metro Manila, Philippines.
  • C. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • D. Letang
    Letang is the surname of Kris Letang, a professional ice hockey defenseman best known for his long career with the NHL’s Pittsburgh Penguins.
  • E. Tangale
    Tangale is a West Chadic language spoken primarily in Gombe State, northeastern Nigeria, by the Tangale people.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b086d6d48190b823ed0a4403fbc5 completed May 3, 2026, 8:31 p.m.
NEDg Description generation batch_69f7b138158c8190957d43d529c37fa4 completed May 3, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69f7b1e2e1b481908b74b5053e49fa38 completed May 3, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:11 p.m.