Triple

T14456664
Position Surface form Disambiguated ID Type / Status
Subject Carolingian court E358475 entity
Predicate notableMember P10 FINISHED
Object Angilbert
Angilbert was a Frankish nobleman, poet, and churchman who served as a close advisor to Charlemagne and later became abbot of the monastery of Saint-Riquier.
 E1100743 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: Angilbert | Statement: [Carolingian court, notableMember, Angilbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Angilbert
Context triple: [Carolingian court, notableMember, Angilbert]
  • A. Giselbert
    Giselbert is a Germanic given name of medieval origin that later evolved into the name Gilbert.
  • B. Warnefrid
    Warnefrid was a Lombard nobleman of the 8th century best known as the father of the historian and monk Paul the Deacon.
  • C. Galfridus
    Galfridus is a masculine given name of Latin origin, historically used in medieval Europe and related to names like Geoffrey.
  • D. Egbert
    Egbert is a small community in Wyoming, United States.
  • E. Egbert
    Egbert was a 9th-century king of Wessex who significantly expanded West Saxon power and laid foundations for the later unification of England.
  • 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: Angilbert
Triple: [Carolingian court, notableMember, Angilbert]
Generated description
Angilbert was a Frankish nobleman, poet, and churchman who served as a close advisor to Charlemagne and later became abbot of the monastery of Saint-Riquier.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Angilbert
Target entity description: Angilbert was a Frankish nobleman, poet, and churchman who served as a close advisor to Charlemagne and later became abbot of the monastery of Saint-Riquier.
  • A. Giselbert
    Giselbert is a Germanic given name of medieval origin that later evolved into the name Gilbert.
  • B. Warnefrid
    Warnefrid was a Lombard nobleman of the 8th century best known as the father of the historian and monk Paul the Deacon.
  • C. Galfridus
    Galfridus is a masculine given name of Latin origin, historically used in medieval Europe and related to names like Geoffrey.
  • D. Egbert
    Egbert is a small community in Wyoming, United States.
  • E. Egbert
    Egbert was a 9th-century king of Wessex who significantly expanded West Saxon power and laid foundations for the later unification of England.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91a9c0d48190ae015e5e0db806ca completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd649177108190be32af72dcae04ee completed May 8, 2026, 4:20 a.m.
NEDg Description generation batch_69fd664347c48190a411141398794b88 completed May 8, 2026, 4:27 a.m.
NED2 Entity disambiguation (via description) batch_69fd66e5d6b08190ad94a6a5f1809c2a completed May 8, 2026, 4:30 a.m.
Created at: April 10, 2026, 1:19 a.m.