Triple

T10682364
Position Surface form Disambiguated ID Type / Status
Subject The Ward E251788 entity
Predicate mainCharacter P1183 FINISHED
Object Kristen
Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
 E878898 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: Kristen | Statement: [The Ward, mainCharacter, Kristen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kristen
Context triple: [The Ward, mainCharacter, Kristen]
  • A. Kristen
    Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
  • B. Kristen
    Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
  • C. Kristen
    Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • D. Kirsten
    Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • E. Krista
    Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
  • 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: Kristen
Triple: [The Ward, mainCharacter, Kristen]
Generated description
Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kristen
Target entity description: Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
  • A. Kristen
    Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
  • B. Kristen
    Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
  • C. Kristen
    Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • D. Kirsten
    Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • E. Krista
    Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fcc30be481909922844b539b622d completed April 9, 2026, 1:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9888cf7b481909de6a4fecb48cf4b completed April 10, 2026, 11:32 p.m.
NEDg Description generation batch_69d98aea391c81909ec64a29053c35c1 completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98c013348819094bde38a057257b4 completed April 10, 2026, 11:47 p.m.
Created at: April 8, 2026, 9:10 p.m.