Triple

T20248695
Position Surface form Disambiguated ID Type / Status
Subject Eli E498491 entity
Predicate character P662 FINISHED
Object Rose Miller
Rose Miller is a fictional character associated with Eli, likely appearing in the same narrative or creative work.
E1445197 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: Rose Miller | Statement: [Eli, character, Rose Miller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rose Miller
Context triple: [Eli, character, Rose Miller]
  • A. June Miller
    June Miller was an influential figure in the bohemian literary circles of early 20th-century New York and Paris, best known as the charismatic and complex muse of writer Henry Miller and a subject in Anaïs Nin’s diaries.
  • B. Faye Miller
    Faye Miller is a market research psychologist who becomes one of Don Draper’s significant romantic partners in the television series "Mad Men."
  • C. Anne Miller
    Anne Miller is best known as the wife of acclaimed Irish-English actor Michael Gambon.
  • D. Shirley Miller
    Shirley Miller is the central protagonist of the crime drama film "Widows," a recently widowed woman who becomes the leader of a heist planned to settle her late husband's debts.
  • E. Lorraine Miller
    Lorraine Miller was an American actress and dancer active in Hollywood films during the 1940s and 1950s.
  • 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: Rose Miller
Triple: [Eli, character, Rose Miller]
Generated description
Rose Miller is a fictional character associated with Eli, likely appearing in the same narrative or creative work.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rose Miller
Target entity description: Rose Miller is a fictional character associated with Eli, likely appearing in the same narrative or creative work.
  • A. June Miller
    June Miller was an influential figure in the bohemian literary circles of early 20th-century New York and Paris, best known as the charismatic and complex muse of writer Henry Miller and a subject in Anaïs Nin’s diaries.
  • B. Faye Miller
    Faye Miller is a market research psychologist who becomes one of Don Draper’s significant romantic partners in the television series "Mad Men."
  • C. Anne Miller
    Anne Miller is best known as the wife of acclaimed Irish-English actor Michael Gambon.
  • D. Shirley Miller
    Shirley Miller is the central protagonist of the crime drama film "Widows," a recently widowed woman who becomes the leader of a heist planned to settle her late husband's debts.
  • E. Lorraine Miller
    Lorraine Miller was an American actress and dancer active in Hollywood films during the 1940s and 1950s.
  • 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a5ce4081908dff86ed4c613fd6 completed April 20, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08d7c821a08190bacd148d57c9be93 completed May 16, 2026, 8:47 p.m.
NEDg Description generation batch_6a08d8aa839c81908be2c3e5c8f54ef5 completed May 16, 2026, 8:50 p.m.
NED2 Entity disambiguation (via description) batch_6a08d9784a08819080de2a65fc129e94 completed May 16, 2026, 8:54 p.m.
Created at: April 11, 2026, 11:41 p.m.