Triple

T13519696
Position Surface form Disambiguated ID Type / Status
Subject Romeo and Juliet (1968 film) E322860 entity
Predicate screenwriter P2831 FINISHED
Object Maura Del Serra
Maura Del Serra is an Italian writer and playwright known for her contributions to contemporary Italian literature and theater.
E1060186 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: Maura Del Serra | Statement: [Romeo and Juliet (1968 film), screenwriter, Maura Del Serra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maura Del Serra
Context triple: [Romeo and Juliet (1968 film), screenwriter, Maura Del Serra]
  • A. Lucia Sciarra
    Lucia Sciarra is a mysterious and seductive widow entangled with the criminal organization SPECTRE in the James Bond film "Spectre."
  • B. Marcella De Marchis
    Marcella De Marchis was an Italian costume and production designer active in mid-20th-century cinema and theater.
  • C. Irene Morra
    Irene Morra is a scholar and editor known for her work on literature and culture, including editing the volume "Road to Morocco."
  • D. Irene Morra
    Irene Morra was a film editor known for her work on early 20th-century American cinema, including the Shirley Temple film "The Little Colonel."
  • E. Anne Rosellini
    Anne Rosellini is an American film producer and screenwriter best known for her collaborations with director Debra Granik on acclaimed independent films.
  • 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: Maura Del Serra
Triple: [Romeo and Juliet (1968 film), screenwriter, Maura Del Serra]
Generated description
Maura Del Serra is an Italian writer and playwright known for her contributions to contemporary Italian literature and theater.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maura Del Serra
Target entity description: Maura Del Serra is an Italian writer and playwright known for her contributions to contemporary Italian literature and theater.
  • A. Lucia Sciarra
    Lucia Sciarra is a mysterious and seductive widow entangled with the criminal organization SPECTRE in the James Bond film "Spectre."
  • B. Marcella De Marchis
    Marcella De Marchis was an Italian costume and production designer active in mid-20th-century cinema and theater.
  • C. Irene Morra
    Irene Morra is a scholar and editor known for her work on literature and culture, including editing the volume "Road to Morocco."
  • D. Irene Morra
    Irene Morra was a film editor known for her work on early 20th-century American cinema, including the Shirley Temple film "The Little Colonel."
  • E. Anne Rosellini
    Anne Rosellini is an American film producer and screenwriter best known for her collaborations with director Debra Granik on acclaimed independent films.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa3df0c8190804174695587f0ea completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a835ea448190a5ddaf8479e0b36c completed May 3, 2026, 7:55 p.m.
NEDg Description generation batch_69f7a91deb3c8190ad2be7f1ca99ac9b completed May 3, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_69f7ad51c6808190afa80fc3622399bf completed May 3, 2026, 8:17 p.m.
Created at: April 9, 2026, 9:44 p.m.