Triple
T3892838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnes |
E88099
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Agnese
Agnese is an Italian given name, equivalent to the English name Agnes, traditionally associated with Christian saints and classical European usage.
|
E396505
|
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: Agnese | Statement: [Agnes, hasVariant, Agnese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agnese Context triple: [Agnes, hasVariant, Agnese]
-
A.
Caterina
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
-
B.
Benedetta
Benedetta is an Italian feminine given name, equivalent to "Benedicta" and commonly used in Italy and other Italian-speaking communities.
-
C.
Giovanna
Giovanna is an Italian feminine given name equivalent to English "Jane," commonly used in Italy and among Italian-speaking communities.
-
D.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
E.
Leonora
Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
- 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: Agnese Triple: [Agnes, hasVariant, Agnese]
Generated description
Agnese is an Italian given name, equivalent to the English name Agnes, traditionally associated with Christian saints and classical European usage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Agnese Target entity description: Agnese is an Italian given name, equivalent to the English name Agnes, traditionally associated with Christian saints and classical European usage.
-
A.
Caterina
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
-
B.
Benedetta
Benedetta is an Italian feminine given name, equivalent to "Benedicta" and commonly used in Italy and other Italian-speaking communities.
-
C.
Giovanna
Giovanna is an Italian feminine given name equivalent to English "Jane," commonly used in Italy and among Italian-speaking communities.
-
D.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
E.
Leonora
Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
- 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_69aed9466d548190939f5217a23ed4ac |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecce860c8190b16eca2e14f6544f |
completed | March 9, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c96ff648190b03807547930d51d |
completed | March 14, 2026, 8:30 a.m. |
| NEDg | Description generation | batch_69b51d14269881909b75083e3928163a |
completed | March 14, 2026, 8:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b51d73ecd48190881c15ff6e0daea0 |
completed | March 14, 2026, 8:33 a.m. |
Created at: March 9, 2026, 3:21 p.m.