Triple

T17751874
Position Surface form Disambiguated ID Type / Status
Subject Gitanas Nausėda E443131 entity
Predicate familyName P18 FINISHED
Object Nausėda
Nausėda is a Lithuanian surname most prominently associated with Gitanas Nausėda, the President of Lithuania.
 E1284796 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: Nausėda | Statement: [Gitanas Nausėda, familyName, Nausėda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nausėda
Context triple: [Gitanas Nausėda, familyName, Nausėda]
  • A. Plungė
    Plungė is a town in northwestern Lithuania that serves as an important cultural and economic center of the Samogitia region.
  • B. Kaunos
    Kaunos is an ancient Carian city in southwestern Turkey, renowned for its rock-cut Lycian tombs, harbor ruins, and archaeological remains near the modern town of Dalyan.
  • C. Velnias
    Velnias is a chthonic deity in Baltic paganism associated with the underworld, the dead, and often trickster-like or demonic qualities.
  • D. Skuodas
    Skuodas is a small historic town in northwestern Lithuania, known as one of the traditional centers of the Samogitian ethnographic region.
  • E. Visaginas
    Visaginas is a town in northeastern Lithuania known for its Soviet-era origins and proximity to the now-decommissioned Ignalina Nuclear Power Plant.
  • 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: Nausėda
Triple: [Gitanas Nausėda, familyName, Nausėda]
Generated description
Nausėda is a Lithuanian surname most prominently associated with Gitanas Nausėda, the President of Lithuania.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nausėda
Target entity description: Nausėda is a Lithuanian surname most prominently associated with Gitanas Nausėda, the President of Lithuania.
  • A. Plungė
    Plungė is a town in northwestern Lithuania that serves as an important cultural and economic center of the Samogitia region.
  • B. Kaunos
    Kaunos is an ancient Carian city in southwestern Turkey, renowned for its rock-cut Lycian tombs, harbor ruins, and archaeological remains near the modern town of Dalyan.
  • C. Velnias
    Velnias is a chthonic deity in Baltic paganism associated with the underworld, the dead, and often trickster-like or demonic qualities.
  • D. Skuodas
    Skuodas is a small historic town in northwestern Lithuania, known as one of the traditional centers of the Samogitian ethnographic region.
  • E. Visaginas
    Visaginas is a town in northeastern Lithuania known for its Soviet-era origins and proximity to the now-decommissioned Ignalina Nuclear Power Plant.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4841b3ccc8190b3241b3e0fa4b2e8 completed April 19, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0243067e6c8190b94113eb4785faae completed May 11, 2026, 8:58 p.m.
NEDg Description generation batch_6a0244ca6b348190a1c68dc3bf873f1d completed May 11, 2026, 9:06 p.m.
NED2 Entity disambiguation (via description) batch_6a024530b5dc8190a4776863cc01babf completed May 11, 2026, 9:08 p.m.
Created at: April 10, 2026, 10:10 a.m.