Triple

T8843547
Position Surface form Disambiguated ID Type / Status
Subject Zola E210446 entity
Predicate mainCharacter P1183 FINISHED
Object Zola
Zola is a fictional character whose name typically serves as the title and central focus of the story in which they appear.
 E210446 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: Zola | Statement: [Zola, mainCharacter, Zola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zola
Context triple: [Zola, mainCharacter, Zola]
  • A. Zola
    Zola is a township neighborhood in Soweto, South Africa, known for its vibrant street culture and significant role in the country’s urban history.
  • B. Zola
    Zola is a 2020 dark comedy-drama film based on a viral Twitter thread, following a Detroit waitress on a chaotic road trip into the world of stripping and crime.
  • C. Zola
    Zola is a French surname most famously borne by Émile Zola, the influential 19th-century novelist and leading figure of literary naturalism.
  • D. Alexandrine Zola
    Alexandrine Zola was the wife of French novelist Émile Zola, known for her long and complex marriage to the prominent naturalist writer and her role in managing his household and legacy.
  • E. Julien
    Julien is a given name of French origin commonly used for males in various Francophone and European countries.
  • 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: Zola
Triple: [Zola, mainCharacter, Zola]
Generated description
Zola is a fictional character whose name typically serves as the title and central focus of the story in which they appear.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zola
Target entity description: Zola is a fictional character whose name typically serves as the title and central focus of the story in which they appear.
  • A. Zola
    Zola is a French surname most famously borne by Émile Zola, the influential 19th-century novelist and leading figure of literary naturalism.
  • B. Zola
    Zola is a township neighborhood in Soweto, South Africa, known for its vibrant street culture and significant role in the country’s urban history.
  • C. Zola chosen
    Zola is a 2020 dark comedy-drama film based on a viral Twitter thread, following a Detroit waitress on a chaotic road trip into the world of stripping and crime.
  • D. Alexandrine Zola
    Alexandrine Zola was the wife of French novelist Émile Zola, known for her long and complex marriage to the prominent naturalist writer and her role in managing his household and legacy.
  • E. Julien
    Julien is a given name of French origin commonly used for males in various Francophone and European countries.
  • F. None of above.

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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc608a73c88190875409fef79ffc8a completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa07ad12c81908de0502706ad4019 completed April 3, 2026, 11:11 a.m.
NEDg Description generation batch_69cfa1714b4081909035c9b15c82c1be completed April 3, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69cfa24be80481909e2b575f99cd1dc4 completed April 3, 2026, 11:19 a.m.
Created at: March 30, 2026, 6:48 p.m.