Triple

T2823419
Position Surface form Disambiguated ID Type / Status
Subject Quinn E54862 entity
Predicate hasVariant P455 FINISHED
Object Quin
Quin is a given name, often used as a variant of Quinn, that can function as a unisex first name or surname.
 E301097 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: Quin | Statement: [Quinn, hasVariant, Quin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Quin
Context triple: [Quinn, hasVariant, Quin]
  • A. Viadrus
    Viadrus is the ancient Latin name historically used to refer to the Oder River in Central Europe.
  • B. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • C. Velkua
    Velkua is a former island municipality in southwestern Finland known for its coastal archipelago landscape in the Baltic Sea.
  • D. Дьокуускай
    Дьокуускай is the Sakha (Yakut) name for Yakutsk, the capital city of Russia’s Sakha Republic in northeastern Siberia.
  • E. Freirina
    Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
  • 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: Quin
Triple: [Quinn, hasVariant, Quin]
Generated description
Quin is a given name, often used as a variant of Quinn, that can function as a unisex first name or surname.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Quin
Target entity description: Quin is a given name, often used as a variant of Quinn, that can function as a unisex first name or surname.
  • A. Viadrus
    Viadrus is the ancient Latin name historically used to refer to the Oder River in Central Europe.
  • B. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • C. Velkua
    Velkua is a former island municipality in southwestern Finland known for its coastal archipelago landscape in the Baltic Sea.
  • D. Дьокуускай
    Дьокуускай is the Sakha (Yakut) name for Yakutsk, the capital city of Russia’s Sakha Republic in northeastern Siberia.
  • E. Freirina
    Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde71fdc08190b18660261fe24adf completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afcead12588190bfbb2c9e93b05e0d completed March 10, 2026, 7:56 a.m.
NEDg Description generation batch_69afcf5ec0a481909061d50877429f3b completed March 10, 2026, 7:59 a.m.
NED2 Entity disambiguation (via description) batch_69afcff778748190978e7d306e0d1ce1 completed March 10, 2026, 8:01 a.m.
Created at: March 6, 2026, 9:59 p.m.