Triple

T19600553
Position Surface form Disambiguated ID Type / Status
Subject Marguerite Churchill E470460 entity
Predicate notableWork P4 FINISHED
Object The Valiant
The Valiant is a 1929 American pre-Code drama film notable for being one of Marguerite Churchill’s early prominent screen roles.
 E1384423 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: The Valiant | Statement: [Marguerite Churchill, notableWork, The Valiant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Valiant
Context triple: [Marguerite Churchill, notableWork, The Valiant]
  • A. The Valiant
    The Valiant is a massive airborne aircraft carrier and command ship used by UNIT in the Doctor Who television series.
  • B. Valiant
    Valiant is the knight-themed mascot representing Manhattanville College’s athletic teams.
  • C. Valiant
    Valiant is the surname of Leslie Valiant, a prominent computer scientist known for his foundational work in computational learning theory and complexity theory.
  • D. The Valiant Years
    The Valiant Years is a historical television documentary series that chronicles Winston Churchill’s leadership and key events of World War II.
  • E. The Hero
    "The Hero" is a poignant World War I poem by Siegfried Sassoon that bitterly exposes the gap between the brutal reality of a soldier’s death and the comforting lies told to those at home.
  • 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: The Valiant
Triple: [Marguerite Churchill, notableWork, The Valiant]
Generated description
The Valiant is a 1929 American pre-Code drama film notable for being one of Marguerite Churchill’s early prominent screen roles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The Valiant
Target entity description: The Valiant is a 1929 American pre-Code drama film notable for being one of Marguerite Churchill’s early prominent screen roles.
  • A. The Valiant
    The Valiant is a massive airborne aircraft carrier and command ship used by UNIT in the Doctor Who television series.
  • B. Valiant
    Valiant is the knight-themed mascot representing Manhattanville College’s athletic teams.
  • C. Valiant
    Valiant is the surname of Leslie Valiant, a prominent computer scientist known for his foundational work in computational learning theory and complexity theory.
  • D. The Valiant Years
    The Valiant Years is a historical television documentary series that chronicles Winston Churchill’s leadership and key events of World War II.
  • E. The Hero
    "The Hero" is a poignant World War I poem by Siegfried Sassoon that bitterly exposes the gap between the brutal reality of a soldier’s death and the comforting lies told to those at home.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6407df98c8190b258ac3b690fe4b1 completed April 20, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a075f1dc2f48190a66d0145b39f06a3 completed May 15, 2026, 5:59 p.m.
NEDg Description generation batch_6a075fbe27a081909c6869abfdfb6079 completed May 15, 2026, 6:02 p.m.
NED2 Entity disambiguation (via description) batch_6a07608dfcb481908833ecb65c10b96b completed May 15, 2026, 6:06 p.m.
Created at: April 10, 2026, 1:43 p.m.