Triple

T30219642
Position Surface form Disambiguated ID Type / Status
Subject Cardinal Benelli in The Last Confession E768306 entity
Predicate basedOn P98 FINISHED
Object Giovanni Benelli
Giovanni Benelli was an Italian cardinal and influential Vatican diplomat who served as a close aide to Pope Paul VI and was considered a leading papal contender in the 1970s.
E2297611 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: Giovanni Benelli | Statement: [Cardinal Benelli in The Last Confession, basedOn, Giovanni Benelli]
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: Giovanni Benelli
Triple: [Cardinal Benelli in The Last Confession, basedOn, Giovanni Benelli]
Generated description
Giovanni Benelli was an Italian cardinal and influential Vatican diplomat who served as a close aide to Pope Paul VI and was considered a leading papal contender in the 1970s.

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_69f2247fd8b8819087fcf83cb7a05eb8 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ff8bc9081909ad67eeac8291bf6 completed May 2, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83b08766bc8190a4a98ac495b552c0 completed Aug. 18, 2026, 1:08 a.m.
NEDg Description generation batch_6a83b1be751c8190ad722369ed00eec9 completed Aug. 18, 2026, 1:13 a.m.
NED2 Entity disambiguation (via description) batch_6a83b216a30c8190b2fb147844b28b46 completed Aug. 18, 2026, 1:15 a.m.
Created at: April 29, 2026, 7:34 p.m.