Triple

T10493979
Position Surface form Disambiguated ID Type / Status
Subject Casualties of War E247486 entity
Predicate leadCharacter P1668 FINISHED
Object Meserve
Meserve is the ruthless and morally corrupt sergeant in the Vietnam War film "Casualties of War," whose actions drive the central conflict of the story.
 E867714 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: Meserve | Statement: [Casualties of War, leadCharacter, Meserve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Meserve
Context triple: [Casualties of War, leadCharacter, Meserve]
  • A. Mattersey
    Mattersey is a small village and civil parish in Nottinghamshire, England, known for its rural setting and historic priory remains.
  • B. Menstrie
    Menstrie is a small village in central Scotland, situated at the foot of the Ochil Hills in Clackmannanshire.
  • C. Mullens
    Mullens is a surname of likely English or Irish origin borne by various individuals and families.
  • D. Midgley
    Midgley is a small village in West Yorkshire, England, known for its rural setting in the Calder Valley near Luddenden Foot.
  • E. Maberly
    Maberly is an English surname most notably associated with actress Polly Maberly, known for her work in British television and film.
  • 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: Meserve
Triple: [Casualties of War, leadCharacter, Meserve]
Generated description
Meserve is the ruthless and morally corrupt sergeant in the Vietnam War film "Casualties of War," whose actions drive the central conflict of the story.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Meserve
Target entity description: Meserve is the ruthless and morally corrupt sergeant in the Vietnam War film "Casualties of War," whose actions drive the central conflict of the story.
  • A. Mattersey
    Mattersey is a small village and civil parish in Nottinghamshire, England, known for its rural setting and historic priory remains.
  • B. Menstrie
    Menstrie is a small village in central Scotland, situated at the foot of the Ochil Hills in Clackmannanshire.
  • C. Mullens
    Mullens is a surname of likely English or Irish origin borne by various individuals and families.
  • D. Midgley
    Midgley is a small village in West Yorkshire, England, known for its rural setting in the Calder Valley near Luddenden Foot.
  • E. Maberly
    Maberly is an English surname most notably associated with actress Polly Maberly, known for her work in British television and film.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097fe2bc81909d66ce43f3533284 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcaeb6088190829b6c26eb1de7d5 completed April 10, 2026, 11:19 a.m.
NEDg Description generation batch_69d8e8c8e360819085376d4c4ea9712d completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901ef24608190934377d9dc855d6f completed April 10, 2026, 1:58 p.m.
Created at: April 6, 2026, 12:24 p.m.