Triple
T7546676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ercole Antonio Mattioli |
E178421
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Mattioli
Mattioli is an Italian surname historically associated with figures such as the 17th-century statesman Ercole Antonio Mattioli.
|
E672576
|
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: Mattioli | Statement: [Ercole Antonio Mattioli, familyName, Mattioli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mattioli Context triple: [Ercole Antonio Mattioli, familyName, Mattioli]
-
A.
Forlani
Forlani is an Italian surname most notably associated with English actress Claire Forlani.
-
B.
Matta
Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
-
C.
Bonomi
Bonomi is an Italian surname most notably associated with Ivanoe Bonomi, a prominent early 20th-century Italian politician and statesman.
-
D.
Zannone
Zannone is a small, uninhabited Italian island in the Tyrrhenian Sea, noted for its protected natural environment and inclusion in the Circeo National Park.
-
E.
Mariani
Mariani is a town in Assam, India, known as a key railway hub in the region.
- 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: Mattioli Triple: [Ercole Antonio Mattioli, familyName, Mattioli]
Generated description
Mattioli is an Italian surname historically associated with figures such as the 17th-century statesman Ercole Antonio Mattioli.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mattioli Target entity description: Mattioli is an Italian surname historically associated with figures such as the 17th-century statesman Ercole Antonio Mattioli.
-
A.
Forlani
Forlani is an Italian surname most notably associated with English actress Claire Forlani.
-
B.
Matta
Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
-
C.
Bonomi
Bonomi is an Italian surname most notably associated with Ivanoe Bonomi, a prominent early 20th-century Italian politician and statesman.
-
D.
Zannone
Zannone is a small, uninhabited Italian island in the Tyrrhenian Sea, noted for its protected natural environment and inclusion in the Circeo National Park.
-
E.
Mariani
Mariani is a town in Assam, India, known as a key railway hub in the region.
- 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_69c69f2cbe08819088f9eb0c03ef529b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f89963ec8190ae7b8a2b9508c074 |
completed | March 27, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856bb83b88190947c0efed84b891a |
completed | March 28, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69c8575116c481909aa2bebb997e2883 |
completed | March 28, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c857d522dc8190ae3c4734ac428334 |
completed | March 28, 2026, 10:36 p.m. |
Created at: March 27, 2026, 3:49 p.m.