Triple

T20525304
Position Surface form Disambiguated ID Type / Status
Subject Franco Fraticelli E503918 entity
Predicate editedFilm P14416 FINISHED
Object Opera
Opera is a 1987 Italian horror film directed by Dario Argento, noted for its stylized violence and psychological terror set in the world of grand opera.
 E1435985 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: Opera | Statement: [Franco Fraticelli, editedFilm, Opera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Opera
Context triple: [Franco Fraticelli, editedFilm, Opera]
  • A. Opera
    Opera is a web browser known for its built-in features like a free VPN, ad blocker, and integrated messaging tools.
  • B. Opera
    Opera is a metro station on Cairo's Line 2 serving the downtown area near the Cairo Opera House and surrounding cultural landmarks.
  • C. Opera
    Opera is a historic Budapest Metro station located beneath Andrássy Avenue, serving the Hungarian State Opera House and the surrounding cultural district.
  • D. Ópera
    Ópera is a central Madrid Metro station located near the historic Teatro Real opera house and Plaza de Oriente.
  • E. OPERA
    OPERA was a long-baseline neutrino oscillation experiment at the Gran Sasso National Laboratory in Italy, designed to detect tau neutrinos in a beam sent from CERN.
  • 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: Opera
Triple: [Franco Fraticelli, editedFilm, Opera]
Generated description
Opera is a 1987 Italian horror film directed by Dario Argento, noted for its stylized violence and psychological terror set in the world of grand opera.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Opera
Target entity description: Opera is a 1987 Italian horror film directed by Dario Argento, noted for its stylized violence and psychological terror set in the world of grand opera.
  • A. Opera
    Opera is a web browser known for its built-in features like a free VPN, ad blocker, and integrated messaging tools.
  • B. Opera
    Opera is a metro station on Cairo's Line 2 serving the downtown area near the Cairo Opera House and surrounding cultural landmarks.
  • C. Opera
    Opera is a historic Budapest Metro station located beneath Andrássy Avenue, serving the Hungarian State Opera House and the surrounding cultural district.
  • D. Ópera
    Ópera is a central Madrid Metro station located near the historic Teatro Real opera house and Plaza de Oriente.
  • E. OPERA
    OPERA was a long-baseline neutrino oscillation experiment at the Gran Sasso National Laboratory in Italy, designed to detect tau neutrinos in a beam sent from CERN.
  • 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_69e0b4b3a6e08190ae663701f50fab8e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a06504b48190b3f1defdc23a47d5 completed April 20, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a089d43c6588190a4be58521ca67698 completed May 16, 2026, 4:37 p.m.
NEDg Description generation batch_6a089e00cde081908dca3893f03e3398 completed May 16, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_6a089e8a05488190b3470f4ffb5927ce completed May 16, 2026, 4:42 p.m.
Created at: April 16, 2026, 11:37 a.m.