Triple

T24243867
Position Surface form Disambiguated ID Type / Status
Subject Anne of Cyprus E603307 entity
Predicate child P120 FINISHED
Object James of Savoy
James of Savoy was a 15th-century Savoyard nobleman and member of the House of Savoy, notable as the son of Anne of Cyprus and a figure in the dynastic politics linking Savoy and the Lusignan line of Cyprus.
E1678159 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: James of Savoy | Statement: [Anne of Cyprus, child, James of Savoy]
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: James of Savoy
Triple: [Anne of Cyprus, child, James of Savoy]
Generated description
James of Savoy was a 15th-century Savoyard nobleman and member of the House of Savoy, notable as the son of Anne of Cyprus and a figure in the dynastic politics linking Savoy and the Lusignan line of Cyprus.

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_69e2953f631c819097cbb421046bd417 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28b82e13c819083ca524e47ed66b1 completed April 29, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10894b99ac81908749abb631e0385a completed May 22, 2026, 4:50 p.m.
NEDg Description generation batch_6a108a0af25481909d520360b86ff170 completed May 22, 2026, 4:53 p.m.
NED2 Entity disambiguation (via description) batch_6a108afb4ad08190a1e9bcd731d98fcb completed May 22, 2026, 4:57 p.m.
Created at: April 18, 2026, 12:04 a.m.