Triple

T10285426
Position Surface form Disambiguated ID Type / Status
Subject Rick's Café Américain E241213 entity
Predicate hasEmployeeInFiction P61558 FINISHED
Object Sascha
Sascha is a fictional bartender and loyal employee at Rick's Café Américain in the classic film "Casablanca."
 E852673 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: Sascha | Statement: [Rick's Café Américain, hasEmployeeInFiction, Sascha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sascha
Context triple: [Rick's Café Américain, hasEmployeeInFiction, Sascha]
  • A. Sasha
    Sasha is a common Russian diminutive form of the given name Alexander (and also Alexandra).
  • B. Sasha
    Sasha is a renowned British DJ and record producer known for his influential role in the development of progressive house and trance music.
  • C. Sasha
    Sasha is one of the costumed cougar mascots representing the University of Houston's athletic teams, the Houston Cougars.
  • D. Kai von Fintel
    Kai von Fintel is a prominent linguist known for his influential work in formal semantics and pragmatics and for his long-standing professorship at MIT.
  • E. Jascha
    Jascha is a given name most famously associated with the legendary violinist Jascha Heifetz.
  • 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: Sascha
Triple: [Rick's Café Américain, hasEmployeeInFiction, Sascha]
Generated description
Sascha is a fictional bartender and loyal employee at Rick's Café Américain in the classic film "Casablanca."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sascha
Target entity description: Sascha is a fictional bartender and loyal employee at Rick's Café Américain in the classic film "Casablanca."
  • A. Sasha
    Sasha is a common Russian diminutive form of the given name Alexander (and also Alexandra).
  • B. Sasha
    Sasha is a renowned British DJ and record producer known for his influential role in the development of progressive house and trance music.
  • C. Sasha
    Sasha is one of the costumed cougar mascots representing the University of Houston's athletic teams, the Houston Cougars.
  • D. Kai von Fintel
    Kai von Fintel is a prominent linguist known for his influential work in formal semantics and pragmatics and for his long-standing professorship at MIT.
  • E. Jascha
    Jascha is a given name most famously associated with the legendary violinist Jascha Heifetz.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4dfbfa26c8190b536655d33112ddf completed April 7, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f8444c48819095100c6d1d45ccc7 completed April 9, 2026, 12:52 a.m.
NEDg Description generation batch_69d6fcae243c819095a2e791716805bd completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd3495fc8190a093d2536cfbe58a completed April 9, 2026, 1:13 a.m.
Created at: April 6, 2026, 11:40 a.m.