Triple

T10337556
Position Surface form Disambiguated ID Type / Status
Subject Hetephernebti E243045 entity
Predicate possibleChild P20843 FINISHED
Object Inetkaes
Inetkaes was an ancient Egyptian royal woman, likely a princess of the early Old Kingdom period.
 E856825 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: Inetkaes | Statement: [Hetephernebti, possibleChild, Inetkaes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Inetkaes
Context triple: [Hetephernebti, possibleChild, Inetkaes]
  • A. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • B. Eketāhuna
    Eketāhuna is a small rural town in New Zealand’s North Island, known for its farming community and location in the Tararua District.
  • C. Siatista
    Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
  • D. Navedenga
    Navedenga is a large-scale, immersive installation by Brazilian artist Ernesto Neto that envelops viewers in a sensorial environment of organic forms, textiles, and spices.
  • E. Nietap
    Nietap is a small village in the Dutch province of Drenthe, known for its rural character and proximity to the town of Roden.
  • 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: Inetkaes
Triple: [Hetephernebti, possibleChild, Inetkaes]
Generated description
Inetkaes was an ancient Egyptian royal woman, likely a princess of the early Old Kingdom period.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Inetkaes
Target entity description: Inetkaes was an ancient Egyptian royal woman, likely a princess of the early Old Kingdom period.
  • A. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • B. Eketāhuna
    Eketāhuna is a small rural town in New Zealand’s North Island, known for its farming community and location in the Tararua District.
  • C. Siatista
    Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
  • D. Navedenga
    Navedenga is a large-scale, immersive installation by Brazilian artist Ernesto Neto that envelops viewers in a sensorial environment of organic forms, textiles, and spices.
  • E. Nietap
    Nietap is a small village in the Dutch province of Drenthe, known for its rural character and proximity to the town of Roden.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e0a3a8e4819097268ce101dec2d1 completed April 7, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7506278f881908b090b13706e5d4e completed April 9, 2026, 7:08 a.m.
NEDg Description generation batch_69d75133588c819093af59327b951cd7 completed April 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69d751d4aa908190a825322ebf0066af completed April 9, 2026, 7:14 a.m.
Created at: April 6, 2026, 11:54 a.m.