Triple
T19282283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muti |
E482218
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Tiberio Muti
Tiberio Muti was an Italian Roman Catholic prelate who served as a cardinal in the early 17th century.
|
E1372585
|
NE FINISHED |
How this triple was built (4 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: Tiberio Muti | Statement: [Muti, hasNotableBearer, Tiberio Muti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiberio Muti Context triple: [Muti, hasNotableBearer, Tiberio Muti]
-
A.
Lorenzo Muti
Lorenzo Muti is the son of renowned Italian conductor Riccardo Muti.
-
B.
Riccardo Muti
Riccardo Muti is an acclaimed Italian conductor renowned for his interpretations of the operatic and symphonic repertoire and for leading major orchestras and opera houses worldwide.
-
C.
Marcello Abbado
Marcello Abbado was an Italian pianist, composer, and conductor known for his contributions to 20th-century classical music and music education.
-
D.
Daniele Gatti
Daniele Gatti is an Italian conductor renowned for leading major European orchestras and opera houses, including a tenure as chief conductor of the Royal Concertgebouw Orchestra.
-
E.
Tommaso Giulini
Tommaso Giulini is an Italian businessman best known as the president and controlling owner of the football club Cagliari Calcio.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Tiberio Muti Triple: [Muti, hasNotableBearer, Tiberio Muti]
Generated description
Tiberio Muti was an Italian Roman Catholic prelate who served as a cardinal in the early 17th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tiberio Muti Target entity description: Tiberio Muti was an Italian Roman Catholic prelate who served as a cardinal in the early 17th century.
-
A.
Lorenzo Muti
Lorenzo Muti is the son of renowned Italian conductor Riccardo Muti.
-
B.
Riccardo Muti
Riccardo Muti is an acclaimed Italian conductor renowned for his interpretations of the operatic and symphonic repertoire and for leading major orchestras and opera houses worldwide.
-
C.
Marcello Abbado
Marcello Abbado was an Italian pianist, composer, and conductor known for his contributions to 20th-century classical music and music education.
-
D.
Daniele Gatti
Daniele Gatti is an Italian conductor renowned for leading major European orchestras and opera houses, including a tenure as chief conductor of the Royal Concertgebouw Orchestra.
-
E.
Tommaso Giulini
Tommaso Giulini is an Italian businessman best known as the president and controlling owner of the football club Cagliari Calcio.
- F. None of above. chosen
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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbffda78819088bf8dbc61756831 |
completed | April 20, 2026, 10:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0723fb4c608190981fd7fc3ff38302 |
completed | May 15, 2026, 1:47 p.m. |
| NEDg | Description generation | batch_6a0725c32c4c8190bb29a764695cd245 |
completed | May 15, 2026, 1:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0726ea260c8190b97e2b18fde36272 |
completed | May 15, 2026, 2 p.m. |
Created at: April 10, 2026, 1:30 p.m.