Triple

T7849078
Position Surface form Disambiguated ID Type / Status
Subject Executive Decision E181997 entity
Predicate mainCharacter P1183 FINISHED
Object Jean
Jean is a central character in the action-thriller film "Executive Decision," involved in the high-stakes mission to thwart a terrorist hijacking.
 E699886 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: Jean | Statement: [Executive Decision, mainCharacter, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jean
Context triple: [Executive Decision, mainCharacter, Jean]
  • A. Jean
    Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • B. Jean
    Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
  • C. Jean
    Jean is a common French given name used for both males and females, equivalent to "John" in English.
  • D. Jean
    Jean is a small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
  • E. Jeanne
    Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • 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: Jean
Triple: [Executive Decision, mainCharacter, Jean]
Generated description
Jean is a central character in the action-thriller film "Executive Decision," involved in the high-stakes mission to thwart a terrorist hijacking.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jean
Target entity description: Jean is a central character in the action-thriller film "Executive Decision," involved in the high-stakes mission to thwart a terrorist hijacking.
  • A. Jean
    Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • B. Jean
    Jean is a small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
  • C. Jean
    Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
  • D. Jean
    Jean is a common French given name used for both males and females, equivalent to "John" in English.
  • E. Jeanne
    Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18e7f5988190808ae4dcfbc06991 completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b0515c08190b866a39749d54849 completed March 31, 2026, 5:26 a.m.
NEDg Description generation batch_69cb762eab0881909c5035b3086dfdd9 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb801cc0c8190864d28e199eb5e67 completed March 31, 2026, 12:03 p.m.
Created at: March 30, 2026, 4:50 p.m.