Triple

T5658860
Position Surface form Disambiguated ID Type / Status
Subject Flemish Limburg E124685 entity
Predicate hasMunicipality P847 FINISHED
Object Kortessem
Kortessem is a small municipality in the Belgian province of Limburg, known for its rural character and historic churches and castles.
E537815 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: Kortessem | Statement: [Flemish Limburg, hasMunicipality, Kortessem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kortessem
Context triple: [Flemish Limburg, hasMunicipality, Kortessem]
  • A. Storslett
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • B. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • C. Slagsvold
    Slagsvold is a Norwegian surname borne by various notable individuals, including figures in academia, politics, and public life.
  • D. Solbo
    Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
  • E. Mosen
    Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
  • 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: Kortessem
Triple: [Flemish Limburg, hasMunicipality, Kortessem]
Generated description
Kortessem is a small municipality in the Belgian province of Limburg, known for its rural character and historic churches and castles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kortessem
Target entity description: Kortessem is a small municipality in the Belgian province of Limburg, known for its rural character and historic churches and castles.
  • A. Storslett
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • B. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • C. Slagsvold
    Slagsvold is a Norwegian surname borne by various notable individuals, including figures in academia, politics, and public life.
  • D. Solbo
    Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
  • E. Mosen
    Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
  • 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_69c0082774a481909d7e63fb2aad56ac completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022fd9b148190bd4aa9c43500949f completed March 22, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04da37ffc819095f33e7e66e7c1d0 completed March 22, 2026, 8:14 p.m.
NEDg Description generation batch_69c04edf30448190a60eda49b8b031a0 completed March 22, 2026, 8:19 p.m.
NED2 Entity disambiguation (via description) batch_69c04fb62690819083327781cb857ccc completed March 22, 2026, 8:23 p.m.
Created at: March 22, 2026, 3:42 p.m.