Triple

T3304160
Position Surface form Disambiguated ID Type / Status
Subject Verdun, France E69406 entity
Predicate hasNearbyDestroyedVillage P23014 FINISHED
Object Ornes
Ornes is a French village in the Meuse department that was completely destroyed during the Battle of Verdun in World War I and left as an uninhabited memorial site.
 E347692 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: Ornes | Statement: [Verdun, France, hasNearbyDestroyedVillage, Ornes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ornes
Context triple: [Verdun, France, hasNearbyDestroyedVillage, Ornes]
  • A. Borge
    Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
  • B. Arne
    Arne is a Scandinavian masculine given name commonly used in Norway, Sweden, and Denmark.
  • C. Solbo
    Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
  • D. Troms
    Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
  • E. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • 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: Ornes
Triple: [Verdun, France, hasNearbyDestroyedVillage, Ornes]
Generated description
Ornes is a French village in the Meuse department that was completely destroyed during the Battle of Verdun in World War I and left as an uninhabited memorial site.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ornes
Target entity description: Ornes is a French village in the Meuse department that was completely destroyed during the Battle of Verdun in World War I and left as an uninhabited memorial site.
  • A. Borge
    Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
  • B. Arne
    Arne is a Scandinavian masculine given name commonly used in Norway, Sweden, and Denmark.
  • C. Solbo
    Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
  • D. Troms
    Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
  • E. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • 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_69ad859f218081909458d2cebbf57565 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0c8179081908a2595d1fdb7560a completed March 8, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3e383088190a056ca793ebf4ffe completed March 12, 2026, 5:12 p.m.
NEDg Description generation batch_69b2f9fb060881909dd940c69cf4a12e completed March 12, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_69b3137bf988819080cef6c1946ec622 completed March 12, 2026, 7:26 p.m.
Created at: March 8, 2026, 3:11 p.m.