Triple

T26621864
Position Surface form Disambiguated ID Type / Status
Subject Giacomo Boncompagni E668220 entity
Predicate child P120 FINISHED
Object Francesco Boncompagni
Francesco Boncompagni was an Italian nobleman of the influential Boncompagni family, descended from Giacomo Boncompagni, the legitimized son of Pope Gregory XIII.
E1758137 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: Francesco Boncompagni | Statement: [Giacomo Boncompagni, child, Francesco Boncompagni]
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: Francesco Boncompagni
Triple: [Giacomo Boncompagni, child, Francesco Boncompagni]
Generated description
Francesco Boncompagni was an Italian nobleman of the influential Boncompagni family, descended from Giacomo Boncompagni, the legitimized son of Pope Gregory XIII.

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_69ee9cff507c819092b95bf7219a702e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615e69e708190af8093e2014052b1 completed May 2, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247da11e0819098453bb1d50bb12b completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a1249b3e9888190b3bae29310007be4 completed May 24, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a124a849c3c81908f1b3acdbaed65f8 completed May 24, 2026, 12:47 a.m.
Created at: April 27, 2026, 2:21 a.m.