Triple

T5957646
Position Surface form Disambiguated ID Type / Status
Subject Sy Bartlett E132555 entity
Predicate spouse P13 FINISHED
Object Ellen Drew
Ellen Drew was an American film actress prominent in the late 1930s and 1940s, known for her roles in Hollywood dramas, comedies, and film noirs.
 E691060 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: Ellen Drew | Statement: [Sy Bartlett, spouse, Ellen Drew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ellen Drew
Context triple: [Sy Bartlett, spouse, Ellen Drew]
  • A. Ellen Andrews
    Ellen Andrews is the mother who magically swaps bodies with her teenage daughter in the 1976 fantasy-comedy film "Freaky Friday."
  • B. Ellen Pierson
    Ellen Pierson is a real estate professional best known for her brief marriage to the late attorney Robert Kardashian, father of the Kardashian family.
  • C. Ellen McHugh
    Ellen McHugh is a fictional character appearing in the 1928 silent drama film "Mother Machree."
  • D. Ellen Lacey
    Ellen Lacey is a fictional character from the 1954 film noir "Crime Wave," involved in the story’s tense criminal underworld and police investigation.
  • E. Ellen Walsh
    Ellen Walsh is a personal name shared by multiple individuals, including professionals and public figures in various fields.
  • 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: Ellen Drew
Triple: [Sy Bartlett, spouse, Ellen Drew]
Generated description
Ellen Drew was an American film actress prominent in the late 1930s and 1940s, known for her roles in Hollywood dramas, comedies, and film noirs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ellen Drew
Target entity description: Ellen Drew was an American film actress prominent in the late 1930s and 1940s, known for her roles in Hollywood dramas, comedies, and film noirs.
  • A. Ellen Andrews
    Ellen Andrews is the mother who magically swaps bodies with her teenage daughter in the 1976 fantasy-comedy film "Freaky Friday."
  • B. Ellen Pierson
    Ellen Pierson is a real estate professional best known for her brief marriage to the late attorney Robert Kardashian, father of the Kardashian family.
  • C. Ellen McHugh
    Ellen McHugh is a fictional character appearing in the 1928 silent drama film "Mother Machree."
  • D. Ellen Lacey
    Ellen Lacey is a fictional character from the 1954 film noir "Crime Wave," involved in the story’s tense criminal underworld and police investigation.
  • E. Ellen Walsh
    Ellen Walsh is a personal name shared by multiple individuals, including professionals and public figures in various fields.
  • 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_69c0086b05cc8190a8f36a96927a525c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039c34ca881909a219eddf99348ab completed March 22, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9660842888190a9d37a5fd1830ccd completed March 29, 2026, 5:48 p.m.
NEDg Description generation batch_69c966ceec808190ac66e8c2d6e876b5 completed March 29, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_69c96800354c8190a71c5a3802de5373 completed March 29, 2026, 5:57 p.m.
Created at: March 22, 2026, 4:02 p.m.