Triple

T3663466
Position Surface form Disambiguated ID Type / Status
Subject Amenhotep II E77704 entity
Predicate child P120 FINISHED
Object Webensenu
Webensenu was an ancient Egyptian prince of the 18th Dynasty, known as a son of Pharaoh Amenhotep II.
 E378648 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: Webensenu | Statement: [Amenhotep II, child, Webensenu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Webensenu
Context triple: [Amenhotep II, child, Webensenu]
  • A. Usingen
    Usingen is a small historic town in the Hochtaunus district of Hesse, Germany, known for its picturesque setting in the Taunus hills and its traditional German architecture.
  • B. Toolbx
    Toolbx is a Fedora project that provides containerized, mutable development environments on otherwise immutable operating systems.
  • C. Wasagaming
    Wasagaming is a small resort and service community that serves as the main visitor hub within Riding Mountain National Park in Manitoba, Canada.
  • D. Kinza Browser
    Kinza Browser is a Japanese-developed, Chromium-based web browser that offers extensive customization options and user-centric features built on the Blink rendering engine.
  • E. Ware
    Ware is a historic market town in Hertfordshire, England, known for its riverside setting on the River Lea and its long-standing role as a local commercial and coaching center.
  • 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: Webensenu
Triple: [Amenhotep II, child, Webensenu]
Generated description
Webensenu was an ancient Egyptian prince of the 18th Dynasty, known as a son of Pharaoh Amenhotep II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Webensenu
Target entity description: Webensenu was an ancient Egyptian prince of the 18th Dynasty, known as a son of Pharaoh Amenhotep II.
  • A. Usingen
    Usingen is a small historic town in the Hochtaunus district of Hesse, Germany, known for its picturesque setting in the Taunus hills and its traditional German architecture.
  • B. Toolbx
    Toolbx is a Fedora project that provides containerized, mutable development environments on otherwise immutable operating systems.
  • C. Wasagaming
    Wasagaming is a small resort and service community that serves as the main visitor hub within Riding Mountain National Park in Manitoba, Canada.
  • D. Kinza Browser
    Kinza Browser is a Japanese-developed, Chromium-based web browser that offers extensive customization options and user-centric features built on the Blink rendering engine.
  • E. Ware
    Ware is a historic market town in Hertfordshire, England, known for its riverside setting on the River Lea and its long-standing role as a local commercial and coaching center.
  • 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_69ad85dfc4dc8190a441864202ab2a7a completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3fcd910819082012b10b23860aa completed March 8, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48848be788190acde46880918d36b completed March 13, 2026, 9:57 p.m.
NEDg Description generation batch_69b489c9a21081908b5e6468205e5c68 completed March 13, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69b4bcaa45cc8190a5db8bfd8845efb1 completed March 14, 2026, 1:40 a.m.
Created at: March 8, 2026, 3:25 p.m.