Triple

T3970933
Position Surface form Disambiguated ID Type / Status
Subject Applause E92332 entity
Predicate starredActor P5563 FINISHED
Object Joan Peers
Joan Peers was an American film actress active in the early 1930s, known for her roles in several pre-Code Hollywood productions.
E404516 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: Joan Peers | Statement: [Applause, starredActor, Joan Peers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joan Peers
Context triple: [Applause, starredActor, Joan Peers]
  • A. Joan Murray
    Joan Murray was the wife of famed British World War II flying ace and double amputee Sir Douglas Bader.
  • B. Joanne Horton
    Joanne Horton was the wife of H. R. Haldeman, a prominent aide to U.S. President Richard Nixon during the Watergate era.
  • C. Joan Barclay
    Joan Barclay was an American film actress known for her numerous roles in low-budget Westerns and B-movies during the 1930s and 1940s.
  • D. Joanne Herring
    Joanne Herring is a Houston socialite, political activist, and businesswoman known for her influential role in supporting U.S. involvement with Afghan resistance fighters during the Soviet–Afghan War.
  • E. Joan Chandler
    Joan Chandler was an American stage and film actress best known for her roles in mid-20th-century dramas and thrillers, including Alfred Hitchcock’s "Rope."
  • 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: Joan Peers
Triple: [Applause, starredActor, Joan Peers]
Generated description
Joan Peers was an American film actress active in the early 1930s, known for her roles in several pre-Code Hollywood productions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Joan Peers
Target entity description: Joan Peers was an American film actress active in the early 1930s, known for her roles in several pre-Code Hollywood productions.
  • A. Joan Murray
    Joan Murray was the wife of famed British World War II flying ace and double amputee Sir Douglas Bader.
  • B. Joanne Horton
    Joanne Horton was the wife of H. R. Haldeman, a prominent aide to U.S. President Richard Nixon during the Watergate era.
  • C. Joan Barclay
    Joan Barclay was an American film actress known for her numerous roles in low-budget Westerns and B-movies during the 1930s and 1940s.
  • D. Joanne Herring
    Joanne Herring is a Houston socialite, political activist, and businesswoman known for her influential role in supporting U.S. involvement with Afghan resistance fighters during the Soviet–Afghan War.
  • E. Joan Chandler
    Joan Chandler was an American stage and film actress best known for her roles in mid-20th-century dramas and thrillers, including Alfred Hitchcock’s "Rope."
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef995d27881908b24a5b2ef57455f completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5400b75d081909b8e4840b15d19f1 completed March 14, 2026, 11:01 a.m.
NEDg Description generation batch_69b540eb53788190aa281ee38edc1729 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b541a55cb081909ec1f87a7553b6f2 completed March 14, 2026, 11:08 a.m.
Created at: March 9, 2026, 3:32 p.m.