Triple

T9871576
Position Surface form Disambiguated ID Type / Status
Subject Lilli Palmer E239968 entity
Predicate givenName P17 FINISHED
Object Lilli
Lilli is a feminine given name, often used in German-speaking and other European countries, and famously borne by the actress Lilli Palmer.
 E825867 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: Lilli | Statement: [Lilli Palmer, givenName, Lilli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lilli
Context triple: [Lilli Palmer, givenName, Lilli]
  • A. Lili
    Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
  • B. Lili
    Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • C. Lilian
    Lilian is the given name of Ethel Lilian Voynich, an English novelist and musician best known for her revolutionary novel "The Gadfly."
  • D. Lillie
    Lillie is the given name of Lillie Hitchcock Coit, a famed 19th-century San Francisco socialite and patron associated with the city’s firefighting history.
  • E. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • 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: Lilli
Triple: [Lilli Palmer, givenName, Lilli]
Generated description
Lilli is a feminine given name, often used in German-speaking and other European countries, and famously borne by the actress Lilli Palmer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lilli
Target entity description: Lilli is a feminine given name, often used in German-speaking and other European countries, and famously borne by the actress Lilli Palmer.
  • A. Lili
    Lili is a 1953 musical fantasy film starring Leslie Caron as a naive orphan who joins a carnival and forms a touching bond with a puppeteer.
  • B. Lili
    Lili is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • C. Lilian
    Lilian is the given name of Ethel Lilian Voynich, an English novelist and musician best known for her revolutionary novel "The Gadfly."
  • D. Lillie
    Lillie is the given name of Lillie Hitchcock Coit, a famed 19th-century San Francisco socialite and patron associated with the city’s firefighting history.
  • E. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • 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_69ca84e7506c819095cbde4ff16512bb completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3f5cc948190b03186b867c92229 completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e46f18148190a36af7e7d7487205 completed April 5, 2026, 4:26 a.m.
NEDg Description generation batch_69d1e5204f748190b1f56ee5469828a2 completed April 5, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69d1e598243481909278cb3c911ce3db completed April 5, 2026, 4:31 a.m.
Created at: March 30, 2026, 8:36 p.m.