Triple

T10954710
Position Surface form Disambiguated ID Type / Status
Subject Donen E258814 entity
Predicate hasVariantSpelling P457 FINISHED
Object Donan
Donan is a variant spelling of the name Donen, which is used as a personal or family name.
 E894963 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: Donan | Statement: [Donen, hasVariantSpelling, Donan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Donan
Context triple: [Donen, hasVariantSpelling, Donan]
  • A. Samil
    Samil is a civil parish located within the municipality of Bragança in northeastern Portugal.
  • B. Yanco
    Yanco is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural activities and irrigation history.
  • C. Geary
    Geary is a small crofting settlement on the Waternish peninsula of the Isle of Skye in Scotland.
  • D. Hejduk
    Hejduk is a surname most notably associated with American soccer player Frankie Hejduk, a former U.S. international and Major League Soccer defender.
  • E. Sindo
    Sindo is an island and administrative division of Ongjin County in Incheon, South Korea, known for its rural landscape and coastal environment.
  • 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: Donan
Triple: [Donen, hasVariantSpelling, Donan]
Generated description
Donan is a variant spelling of the name Donen, which is used as a personal or family name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Donan
Target entity description: Donan is a variant spelling of the name Donen, which is used as a personal or family name.
  • A. Samil
    Samil is a civil parish located within the municipality of Bragança in northeastern Portugal.
  • B. Yanco
    Yanco is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural activities and irrigation history.
  • C. Geary
    Geary is a small crofting settlement on the Waternish peninsula of the Isle of Skye in Scotland.
  • D. Hejduk
    Hejduk is a surname most notably associated with American soccer player Frankie Hejduk, a former U.S. international and Major League Soccer defender.
  • E. Sindo
    Sindo is an island and administrative division of Ongjin County in Incheon, South Korea, known for its rural landscape and coastal environment.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ff718c81909d4baebea3b56b83 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c72196c8190b2336a130b64ab8e completed April 17, 2026, 1:58 p.m.
NEDg Description generation batch_69e24543bd2c8190a3c807baa76c30f6 completed April 17, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_69e25d11ef24819091e730ae2416a058 completed April 17, 2026, 4:17 p.m.
Created at: April 8, 2026, 9:23 p.m.