Triple
T12603708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nerio I Acciaioli |
E300920
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Nerio
Nerio is an Italian masculine given name of ancient origin, historically borne by several notable figures including medieval nobles.
|
E993947
|
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: Nerio | Statement: [Nerio I Acciaioli, givenName, Nerio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nerio Context triple: [Nerio I Acciaioli, givenName, Nerio]
-
A.
Neroni
Neroni is the surname of Madeline Neroni, a fictional character known for her beauty, charm, and manipulative influence in Anthony Trollope’s novel "Barchester Towers."
-
B.
Anilio
Anilio is a mountain village in the Metsovo region of Epirus in northwestern Greece, known for its traditional architecture and alpine setting.
-
C.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
-
D.
Marino
Marino is a surname most famously associated with Dan Marino, the Hall of Fame former NFL quarterback for the Miami Dolphins.
-
E.
Marino
Marino is a historic town in Italy’s Alban Hills near Rome, known for its wine production and annual grape festival.
- 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: Nerio Triple: [Nerio I Acciaioli, givenName, Nerio]
Generated description
Nerio is an Italian masculine given name of ancient origin, historically borne by several notable figures including medieval nobles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nerio Target entity description: Nerio is an Italian masculine given name of ancient origin, historically borne by several notable figures including medieval nobles.
-
A.
Neroni
Neroni is the surname of Madeline Neroni, a fictional character known for her beauty, charm, and manipulative influence in Anthony Trollope’s novel "Barchester Towers."
-
B.
Anilio
Anilio is a mountain village in the Metsovo region of Epirus in northwestern Greece, known for its traditional architecture and alpine setting.
-
C.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
-
D.
Marino
Marino is a surname most famously associated with Dan Marino, the Hall of Fame former NFL quarterback for the Miami Dolphins.
-
E.
Marino
Marino is a historic town in Italy’s Alban Hills near Rome, known for its wine production and annual grape festival.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ecb09e481909d688f174372dde7 |
completed | May 2, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f65fd6fa8c819094a31f8c2d8ee72d |
completed | May 2, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f663fe2fac8190bb70c8f1b919d657 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 9, 2026, 5:10 p.m.