Triple

T26512056
Position Surface form Disambiguated ID Type / Status
Subject Giza royal family E669709 entity
Predicate notableMember P10 FINISHED
Object Prince Nebemakhet
Prince Nebemakhet was an ancient Egyptian royal, likely a son of Pharaoh Khafre, known from his tomb at Giza and his prominent role within the 4th Dynasty court.
E1783474 NE FINISHED

How this triple was built (2 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: Prince Nebemakhet | Statement: [Giza royal family, notableMember, Prince Nebemakhet]
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: Prince Nebemakhet
Triple: [Giza royal family, notableMember, Prince Nebemakhet]
Generated description
Prince Nebemakhet was an ancient Egyptian royal, likely a son of Pharaoh Khafre, known from his tomb at Giza and his prominent role within the 4th Dynasty court.

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_69eeb319ec70819090834c2591cf5f1e completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61392ec5081909382ace560650d77 completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da6108cc8190a55fc00311abd55d completed May 24, 2026, 11 a.m.
NEDg Description generation batch_6a12daf3e7948190bb82f9eac6800971 completed May 24, 2026, 11:03 a.m.
NED2 Entity disambiguation (via description) batch_6a12db74542081909ede3d27600fb26b completed May 24, 2026, 11:05 a.m.
Created at: April 27, 2026, 1:21 a.m.