Triple

T7958657
Position Surface form Disambiguated ID Type / Status
Subject IJsselvallei E184804 entity
Predicate hasPart P35 FINISHED
Object Hattem
Hattem is a historic Dutch town in the province of Gelderland, known for its medieval center and location along the river IJssel.
 E704009 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: Hattem | Statement: [IJsselvallei, hasPart, Hattem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hattem
Context triple: [IJsselvallei, hasPart, Hattem]
  • A. Hassel
    Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
  • B. Harskamp
    Harskamp is a village in the Dutch province of Gelderland, known for its rural character and proximity to the Hoge Veluwe National Park.
  • C. Haselhorst
    Haselhorst is a residential and industrial locality in the Spandau borough of Berlin, Germany, known for its housing estates and proximity to the River Havel.
  • D. Hassela
    Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
  • E. Hodenhagen
    Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • 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: Hattem
Triple: [IJsselvallei, hasPart, Hattem]
Generated description
Hattem is a historic Dutch town in the province of Gelderland, known for its medieval center and location along the river IJssel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hattem
Target entity description: Hattem is a historic Dutch town in the province of Gelderland, known for its medieval center and location along the river IJssel.
  • A. Hassel
    Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
  • B. Harskamp
    Harskamp is a village in the Dutch province of Gelderland, known for its rural character and proximity to the Hoge Veluwe National Park.
  • C. Haselhorst
    Haselhorst is a residential and industrial locality in the Spandau borough of Berlin, Germany, known for its housing estates and proximity to the River Havel.
  • D. Hassela
    Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
  • E. Hodenhagen
    Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • 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_69ca8293a2388190aace944d7ed9c0c0 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b80050c81909b2db95ade495052 completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe07d31a881909e891fdd73c4467b completed March 31, 2026, 2:55 p.m.
NEDg Description generation batch_69cbe554dfd881909edf2c20a7035f17 completed March 31, 2026, 3:16 p.m.
NED2 Entity disambiguation (via description) batch_69cc3429f4148190981d30c3cc4c3c9a completed March 31, 2026, 8:52 p.m.
Created at: March 30, 2026, 5:11 p.m.