Triple

T29736999
Position Surface form Disambiguated ID Type / Status
Subject Grand Cross of the Military Order of Savoy E752489 entity
Predicate class P87 FINISHED
Object Grand Cross
The Grand Cross is the highest and most prestigious class within many chivalric and military orders, typically reserved for individuals of exceptional rank or merit.
E309887 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: Grand Cross | Statement: [Grand Cross of the Military Order of Savoy, class, Grand Cross]
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: Grand Cross
Triple: [Grand Cross of the Military Order of Savoy, class, Grand Cross]
Generated description
The Grand Cross is the highest and most prestigious class within many chivalric and military orders, typically reserved for individuals of exceptional rank or merit.

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_69f0d62a36a88190bf860f00da433ff8 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f67334fe2081908edc2dcea6e231a6 completed May 2, 2026, 9:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa81d44c8190ba6a2764ab936e05 completed June 8, 2026, 11:41 a.m.
NEDg Description generation batch_6a26b058df8c819092e2cd55bf17a5cb completed June 8, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a26b495ec448190ac88779dae9a72dc completed June 8, 2026, 12:24 p.m.
Created at: April 28, 2026, 7:45 p.m.