Triple
T9385866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paper Girls (TV series) |
E225901
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object |
Fina Strazza
Fina Strazza is an American actress best known for her starring role in the science fiction television series "Paper Girls."
|
E796043
|
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: Fina Strazza | Statement: [Paper Girls (TV series), leadActor, Fina Strazza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fina Strazza Context triple: [Paper Girls (TV series), leadActor, Fina Strazza]
-
A.
Daniela Farinacci
Daniela Farinacci is an Australian actress known for her work in film, television, and theatre, including a notable role in the acclaimed drama "Lantana."
-
B.
Giuliana Pozzo
Giuliana Pozzo is a member of the historically prominent Pozzo family, known for its influence and legacy in Italian cultural and social circles.
-
C.
Maria Ferrari
Maria Ferrari is known as the spouse of Australian film director Phillip Noyce.
-
D.
Irene Gamba
Irene Gamba is an Argentine-American mathematician known for her contributions to kinetic theory, partial differential equations, and applied mathematics.
-
E.
Daniela Bianchi
Daniela Bianchi is an Italian actress and former model best known for playing Bond girl Tatiana Romanova in the James Bond film "From Russia with Love" (1963).
- 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: Fina Strazza Triple: [Paper Girls (TV series), leadActor, Fina Strazza]
Generated description
Fina Strazza is an American actress best known for her starring role in the science fiction television series "Paper Girls."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fina Strazza Target entity description: Fina Strazza is an American actress best known for her starring role in the science fiction television series "Paper Girls."
-
A.
Daniela Farinacci
Daniela Farinacci is an Australian actress known for her work in film, television, and theatre, including a notable role in the acclaimed drama "Lantana."
-
B.
Giuliana Pozzo
Giuliana Pozzo is a member of the historically prominent Pozzo family, known for its influence and legacy in Italian cultural and social circles.
-
C.
Maria Ferrari
Maria Ferrari is known as the spouse of Australian film director Phillip Noyce.
-
D.
Irene Gamba
Irene Gamba is an Argentine-American mathematician known for her contributions to kinetic theory, partial differential equations, and applied mathematics.
-
E.
Daniela Bianchi
Daniela Bianchi is an Italian actress and former model best known for playing Bond girl Tatiana Romanova in the James Bond film "From Russia with Love" (1963).
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d3964c8190b0353f56df755db8 |
completed | April 1, 2026, 5:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100eb108c8190add5bacfea1f800a |
completed | April 4, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_69d1017a36e0819091bd6d7bc75d1a97 |
completed | April 4, 2026, 12:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d10270f9948190bbf937089f88bacf |
completed | April 4, 2026, 12:22 p.m. |
Created at: March 30, 2026, 7:44 p.m.