Triple

T1198340
Position Surface form Disambiguated ID Type / Status
Subject Sicario E25718 entity
Predicate character P662 FINISHED
Object Kate Macer
Kate Macer is an idealistic FBI agent who becomes embroiled in a morally ambiguous joint task force targeting Mexican drug cartels in the film "Sicario."
E251909 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: Kate Macer | Statement: [Sicario, character, Kate Macer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Macer
Context triple: [Sicario, character, Kate Macer]
  • A. Kate Garvey
    Kate Garvey is a British public relations executive and former political aide, known for her work with Tony Blair and her marriage to Wikipedia co-founder Jimmy Wales.
  • B. Kat C. Howard
    Kat C. Howard is the wife of American actor Clint Howard.
  • C. Maggie McOmie
    Maggie McOmie is an American actress best known for her role as LUH 3417 in George Lucas's 1971 science fiction film THX 1138.
  • D. Bridget Dryden
    Bridget Dryden was the mother of the notable Puritan spiritual leader and religious dissenter Anne Hutchinson.
  • E. Emily Carmichael
    Emily Carmichael is an American filmmaker and screenwriter known for her work on genre films such as Pacific Rim: Uprising and for her distinctive, imaginative storytelling style.
  • 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: Kate Macer
Triple: [Sicario, character, Kate Macer]
Generated description
Kate Macer is an idealistic FBI agent who becomes embroiled in a morally ambiguous joint task force targeting Mexican drug cartels in the film "Sicario."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kate Macer
Target entity description: Kate Macer is an idealistic FBI agent who becomes embroiled in a morally ambiguous joint task force targeting Mexican drug cartels in the film "Sicario."
  • A. Kate Garvey
    Kate Garvey is a British public relations executive and former political aide, known for her work with Tony Blair and her marriage to Wikipedia co-founder Jimmy Wales.
  • B. Kat C. Howard
    Kat C. Howard is the wife of American actor Clint Howard.
  • C. Maggie McOmie
    Maggie McOmie is an American actress best known for her role as LUH 3417 in George Lucas's 1971 science fiction film THX 1138.
  • D. Bridget Dryden
    Bridget Dryden was the mother of the notable Puritan spiritual leader and religious dissenter Anne Hutchinson.
  • E. Emily Carmichael
    Emily Carmichael is an American filmmaker and screenwriter known for her work on genre films such as Pacific Rim: Uprising and for her distinctive, imaginative storytelling style.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9c013c8190822d44d465d60fdb completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae7ebe47f081909d53dead07879b77 completed March 9, 2026, 8:03 a.m.
NEDg Description generation batch_69ae7f56aa7c8190a889d830303cc669 completed March 9, 2026, 8:05 a.m.
NED2 Entity disambiguation (via description) batch_69ae800868948190a5504969c4cabb7d completed March 9, 2026, 8:08 a.m.
Created at: March 1, 2026, 7:46 p.m.