Triple
T12603846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger of Lauria |
E300922
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object |
Bella d’Amico
Bella d’Amico was a medieval noblewoman known primarily as the mother of the famed Aragonese admiral Roger of Lauria.
|
E993954
|
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: Bella d’Amico | Statement: [Roger of Lauria, parent, Bella d’Amico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bella d’Amico Context triple: [Roger of Lauria, parent, Bella d’Amico]
-
A.
Rosario Bellini
Rosario Bellini was the father of the renowned Italian opera composer Vincenzo Bellini.
-
B.
Margherita Dall’Aglio
Margherita Dall’Aglio was the wife of renowned Italian typographer and printer Giambattista Bodoni.
-
C.
Jina Panebianco
Jina Panebianco is a film and television producer known for co-founding Passionflix, a streaming platform dedicated to romance content.
-
D.
Anna Maria Alberghetti
Anna Maria Alberghetti is an Italian-born American soprano and actress who gained fame as a child prodigy in music and later as a star of film, television, and Broadway.
-
E.
Rosella Postorino
Rosella Postorino is an Italian novelist and translator acclaimed for her psychologically rich fiction, including the award-winning novel "Le assaggiatrici" ("The Women at Hitler’s Table").
- 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: Bella d’Amico Triple: [Roger of Lauria, parent, Bella d’Amico]
Generated description
Bella d’Amico was a medieval noblewoman known primarily as the mother of the famed Aragonese admiral Roger of Lauria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bella d’Amico Target entity description: Bella d’Amico was a medieval noblewoman known primarily as the mother of the famed Aragonese admiral Roger of Lauria.
-
A.
Rosario Bellini
Rosario Bellini was the father of the renowned Italian opera composer Vincenzo Bellini.
-
B.
Margherita Dall’Aglio
Margherita Dall’Aglio was the wife of renowned Italian typographer and printer Giambattista Bodoni.
-
C.
Jina Panebianco
Jina Panebianco is a film and television producer known for co-founding Passionflix, a streaming platform dedicated to romance content.
-
D.
Anna Maria Alberghetti
Anna Maria Alberghetti is an Italian-born American soprano and actress who gained fame as a child prodigy in music and later as a star of film, television, and Broadway.
-
E.
Rosella Postorino
Rosella Postorino is an Italian novelist and translator acclaimed for her psychologically rich fiction, including the award-winning novel "Le assaggiatrici" ("The Women at Hitler’s Table").
- 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.