Triple

T1575838
Position Surface form Disambiguated ID Type / Status
Subject Halvdan Koht E33648 entity
Predicate familyName P18 FINISHED
Object Koht
Koht is a Norwegian surname most notably associated with historian and politician Halvdan Koht.
 E179772 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: Koht | Statement: [Halvdan Koht, familyName, Koht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Koht
Context triple: [Halvdan Koht, familyName, Koht]
  • A. Kohat
    Kohat is a historic city in northwestern Pakistan known for its strategic location, military cantonment, and role as a regional administrative and commercial center.
  • B. Kut
    Kut is a city in eastern Iraq situated on the banks of the Tigris River, known historically as a strategic location and the site of significant World War I battles.
  • C. Kencot
    Kencot is a small rural village in Oxfordshire, England, known for its historic stone cottages and traditional Cotswold character.
  • D. Koreiz
    Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
  • E. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • 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: Koht
Triple: [Halvdan Koht, familyName, Koht]
Generated description
Koht is a Norwegian surname most notably associated with historian and politician Halvdan Koht.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Koht
Target entity description: Koht is a Norwegian surname most notably associated with historian and politician Halvdan Koht.
  • A. Kohat
    Kohat is a historic city in northwestern Pakistan known for its strategic location, military cantonment, and role as a regional administrative and commercial center.
  • B. Kut
    Kut is a city in eastern Iraq situated on the banks of the Tigris River, known historically as a strategic location and the site of significant World War I battles.
  • C. Kencot
    Kencot is a small rural village in Oxfordshire, England, known for its historic stone cottages and traditional Cotswold character.
  • D. Koreiz
    Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
  • E. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • 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_69a885f27a4c8190a4622252cdf54c00 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908d2cffc819090f3d5cbebae3307 completed March 5, 2026, 4:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad402b44688190b02e6d146f009854 completed March 8, 2026, 9:23 a.m.
NEDg Description generation batch_69ad410ba7f881909dcee6e6fd56490f completed March 8, 2026, 9:27 a.m.
NED2 Entity disambiguation (via description) batch_69ad41ff0b0c8190b5429ed6952a0ce6 completed March 8, 2026, 9:31 a.m.
Created at: March 4, 2026, 7:27 p.m.