Triple

T7392005
Position Surface form Disambiguated ID Type / Status
Subject Hawise de Beaumont E170522 entity
Predicate givenName P17 FINISHED
Object Hawise
Hawise is a medieval European female given name borne by several noblewomen in England and France.
 E662615 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: Hawise | Statement: [Hawise de Beaumont, givenName, Hawise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hawise
Context triple: [Hawise de Beaumont, givenName, Hawise]
  • A. Tesseney
    Tesseney is a town in western Eritrea near the Sudanese border, serving as a local commercial and agricultural center in the Gash-Barka region.
  • B. Hannington
    Hannington is a small rural village in Wiltshire, England, known for its traditional English countryside setting and historic character.
  • C. Umberleigh
    Umberleigh is a small rural village in North Devon, England, situated on the River Taw and served by a local railway station.
  • D. Hellingly
    Hellingly is a village and civil parish in East Sussex, England, known for its rural character and historic parish church.
  • E. Collishaw
    Collishaw is a surname most notably associated with Raymond Collishaw, a distinguished Canadian fighter ace of the First World War.
  • 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: Hawise
Triple: [Hawise de Beaumont, givenName, Hawise]
Generated description
Hawise is a medieval European female given name borne by several noblewomen in England and France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hawise
Target entity description: Hawise is a medieval European female given name borne by several noblewomen in England and France.
  • A. Tesseney
    Tesseney is a town in western Eritrea near the Sudanese border, serving as a local commercial and agricultural center in the Gash-Barka region.
  • B. Hannington
    Hannington is a small rural village in Wiltshire, England, known for its traditional English countryside setting and historic character.
  • C. Umberleigh
    Umberleigh is a small rural village in North Devon, England, situated on the River Taw and served by a local railway station.
  • D. Hellingly
    Hellingly is a village and civil parish in East Sussex, England, known for its rural character and historic parish church.
  • E. Collishaw
    Collishaw is a surname most notably associated with Raymond Collishaw, a distinguished Canadian fighter ace of the First World War.
  • 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_69c68a5e2c9081909e713ce866e0060a completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f22318108190a4dde257fe9e947f completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c810f2bff4819093b0082dec4ee773 completed March 28, 2026, 5:33 p.m.
NEDg Description generation batch_69c814ff89708190a6a626ac204f8c6b completed March 28, 2026, 5:50 p.m.
NED2 Entity disambiguation (via description) batch_69c819174bc48190b5575818ccc2f144 completed March 28, 2026, 6:08 p.m.
Created at: March 27, 2026, 3:09 p.m.