Triple

T26418858
Position Surface form Disambiguated ID Type / Status
Subject Senedj E664175 entity
Predicate possibleVariantName P104759 FINISHED
Object Senedes
Senedes is an alternative rendering of the name of the ancient Egyptian pharaoh Senedj, a little-known ruler of Egypt’s Second Dynasty.
E453012 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: Senedes | Statement: [Senedj, possibleVariantName, Senedes]
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: Senedes
Triple: [Senedj, possibleVariantName, Senedes]
Generated description
Senedes is an alternative rendering of the name of the ancient Egyptian pharaoh Senedj, a little-known ruler of Egypt’s Second Dynasty.

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_69ee883a04ec81908883c4559f8c7e24 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f660f633f08190b756f70258db804b completed May 2, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11bb1290408190945222767430c2da completed May 23, 2026, 2:34 p.m.
NEDg Description generation batch_6a11be5f621881908d83370dd283a10f completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf7e1de48190ba8ed044628d5bf7 completed May 23, 2026, 2:53 p.m.
Created at: April 26, 2026, 11:42 p.m.