Triple

T31729498
Position Surface form Disambiguated ID Type / Status
Subject Carrara family of Padua E809819 entity
Predicate alsoKnownAs P39 FINISHED
Object Carraresi
The Carraresi were a powerful medieval noble dynasty that ruled the Italian city of Padua during the 14th century.
E1992133 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: Carraresi | Statement: [Carrara family of Padua, alsoKnownAs, Carraresi]
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: Carraresi
Triple: [Carrara family of Padua, alsoKnownAs, Carraresi]
Generated description
The Carraresi were a powerful medieval noble dynasty that ruled the Italian city of Padua during the 14th century.

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_69f348e0e4908190a884582eca646fb7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6ab1d46a4819098cbd250564c7d85 completed May 3, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eddc563188190a63e917e15c11cd2 completed June 14, 2026, 4:58 p.m.
NEDg Description generation batch_6a2ee18ef3b48190ae416a1eb5688057 completed June 14, 2026, 5:14 p.m.
NED2 Entity disambiguation (via description) batch_6a2eec652bc4819084acc69f5da6c44c completed June 14, 2026, 6:01 p.m.
Created at: April 30, 2026, 11:21 p.m.