Triple

T15088614
Position Surface form Disambiguated ID Type / Status
Subject Kenan Evren E360351 entity
Predicate familyName P18 FINISHED
Object Evren
Evren is a Turkish surname most notably associated with Kenan Evren, the former military leader and seventh President of Turkey.
E1136981 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: Evren | Statement: [Kenan Evren, familyName, Evren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Evren
Context triple: [Kenan Evren, familyName, Evren]
  • A. Universo
    Universo is a U.S.-based Spanish-language cable television network owned by NBCUniversal that features sports, entertainment, and music programming aimed primarily at Latino audiences.
  • B. Erdek
    Erdek is a coastal town and popular seaside resort in Turkey’s Balıkesir Province, located on the Kapıdağ Peninsula along the Sea of Marmara.
  • C. Kosmos
    Kosmos is Alexander von Humboldt’s multi-volume work that presents a comprehensive scientific and philosophical overview of the natural world and the universe.
  • D. Mahaprithibi
    Mahaprithibi is a celebrated Bengali poetry collection by Jibanananda Das that reflects his modernist style and introspective, evocative imagery.
  • E. Verden
    Verden is a historic town in Lower Saxony, Germany, known for its medieval cathedral and location along the Weser River.
  • 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: Evren
Triple: [Kenan Evren, familyName, Evren]
Generated description
Evren is a Turkish surname most notably associated with Kenan Evren, the former military leader and seventh President of Turkey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Evren
Target entity description: Evren is a Turkish surname most notably associated with Kenan Evren, the former military leader and seventh President of Turkey.
  • A. Universo
    Universo is a U.S.-based Spanish-language cable television network owned by NBCUniversal that features sports, entertainment, and music programming aimed primarily at Latino audiences.
  • B. Erdek
    Erdek is a coastal town and popular seaside resort in Turkey’s Balıkesir Province, located on the Kapıdağ Peninsula along the Sea of Marmara.
  • C. Kosmos
    Kosmos is Alexander von Humboldt’s multi-volume work that presents a comprehensive scientific and philosophical overview of the natural world and the universe.
  • D. Mahaprithibi
    Mahaprithibi is a celebrated Bengali poetry collection by Jibanananda Das that reflects his modernist style and introspective, evocative imagery.
  • E. Verden
    Verden is a historic town in Lower Saxony, Germany, known for its medieval cathedral and location along the Weser River.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00277ea808190be3f002a8316eff1 completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae1ba4208190b1e8c55668a1b422 completed May 9, 2026, 3:46 a.m.
NEDg Description generation batch_69feb10161fc81908aef193552ada55b completed May 9, 2026, 3:58 a.m.
NED2 Entity disambiguation (via description) batch_69feb168eac0819098bd76bac6daa838 completed May 9, 2026, 4 a.m.
Created at: April 10, 2026, 3:04 a.m.