Triple

T5683123
Position Surface form Disambiguated ID Type / Status
Subject La Dolce Vita E125244 entity
Predicate distributor P1951 FINISHED
Object Cineriz
Cineriz was an Italian film production and distribution company known for handling prominent auteur films during the mid-20th century.
 E539888 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: Cineriz | Statement: [La Dolce Vita, distributor, Cineriz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cineriz
Context triple: [La Dolce Vita, distributor, Cineriz]
  • A. Tourangelle
    Tourangelle is the French term for a female inhabitant or native of the city of Tours in central France.
  • B. Candalus
    Candalus is a figure from Greek mythology known as a son of Rhode.
  • C. The Turim
    The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
  • D. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • E. Terik
    Terik is a Southern Nilotic language spoken by the Terik people of western Kenya, closely related to Nandi and other Kalenjin languages.
  • 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: Cineriz
Triple: [La Dolce Vita, distributor, Cineriz]
Generated description
Cineriz was an Italian film production and distribution company known for handling prominent auteur films during the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cineriz
Target entity description: Cineriz was an Italian film production and distribution company known for handling prominent auteur films during the mid-20th century.
  • A. Tourangelle
    Tourangelle is the French term for a female inhabitant or native of the city of Tours in central France.
  • B. Candalus
    Candalus is a figure from Greek mythology known as a son of Rhode.
  • C. The Turim
    The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
  • D. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • E. Terik
    Terik is a Southern Nilotic language spoken by the Terik people of western Kenya, closely related to Nandi and other Kalenjin languages.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023b780248190a912d2dddbd0aa17 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a39756c819098b06911c58d50a8 completed March 22, 2026, 9:08 p.m.
NEDg Description generation batch_69c05d5cce248190abf49b02513fe06e completed March 22, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69c05e061ff88190b9387358cc8bc199 completed March 22, 2026, 9:24 p.m.
Created at: March 22, 2026, 3:44 p.m.