Triple

T6027287
Position Surface form Disambiguated ID Type / Status
Subject Charles the Simple E134211 entity
Predicate spouse P13 FINISHED
Object Frederuna
Frederuna was a 10th-century Frankish queen consort of West Francia as the first wife of King Charles the Simple.
 E563498 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: Frederuna | Statement: [Charles the Simple, spouse, Frederuna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Frederuna
Context triple: [Charles the Simple, spouse, Frederuna]
  • A. Freirina
    Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
  • B. Renaelva
    Renaelva is a river in eastern Norway that flows through Hedmark county before joining the larger Glomma river.
  • C. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • D. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • E. Nerissa
    Nerissa is a witty and loyal lady-in-waiting to Portia in Shakespeare’s play "The Merchant of Venice," known for her intelligence, humor, and role in the play’s romantic subplots.
  • 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: Frederuna
Triple: [Charles the Simple, spouse, Frederuna]
Generated description
Frederuna was a 10th-century Frankish queen consort of West Francia as the first wife of King Charles the Simple.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Frederuna
Target entity description: Frederuna was a 10th-century Frankish queen consort of West Francia as the first wife of King Charles the Simple.
  • A. Freirina
    Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
  • B. Renaelva
    Renaelva is a river in eastern Norway that flows through Hedmark county before joining the larger Glomma river.
  • C. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • D. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • E. Nerissa
    Nerissa is a witty and loyal lady-in-waiting to Portia in Shakespeare’s play "The Merchant of Venice," known for her intelligence, humor, and role in the play’s romantic subplots.
  • 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_69c0087515148190a97475d412563865 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0560cdc308190b25ca8ecb42c4e4f completed March 22, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c113799d648190a08516a33a5f92b7 completed March 23, 2026, 10:18 a.m.
NEDg Description generation batch_69c113c9bc048190ab517300d56dd8e0 completed March 23, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_69c1144e77f881908ab59a67160c1630 completed March 23, 2026, 10:22 a.m.
Created at: March 22, 2026, 4:07 p.m.