Triple

T5160678
Position Surface form Disambiguated ID Type / Status
Subject Fast X E116426 entity
Predicate featuresCharacter P626 FINISHED
Object Tess
Tess is a character in the action film "Fast X," part of the long-running Fast & Furious franchise.
 E499469 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: Tess | Statement: [Fast X, featuresCharacter, Tess]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tess
Context triple: [Fast X, featuresCharacter, Tess]
  • A. Tess
    Tess is a 1979 period drama film directed by Roman Polanski, adapted from Thomas Hardy’s novel "Tess of the d'Urbervilles."
  • B. Tess
    Tess is a central character in the musical film "Burlesque," serving as the tough but caring owner and manager of the struggling burlesque club.
  • C. Far from the Madding Crowd
    Far from the Madding Crowd is an 1874 novel by Thomas Hardy that follows the romantic and social entanglements of the independent Bathsheba Everdene in rural Victorian England.
  • D. The Farmer’s Daughter
    The Farmer’s Daughter is a 1947 American romantic comedy film starring Loretta Young as a Swedish-American farm girl who becomes involved in politics.
  • E. Ethan Frome
    Ethan Frome is a 1993 American drama film directed by John Madden, adapted from Edith Wharton's novel about a tragic love triangle in a bleak New England setting.
  • 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: Tess
Triple: [Fast X, featuresCharacter, Tess]
Generated description
Tess is a character in the action film "Fast X," part of the long-running Fast & Furious franchise.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tess
Target entity description: Tess is a character in the action film "Fast X," part of the long-running Fast & Furious franchise.
  • A. Tess
    Tess is a central character in the musical film "Burlesque," serving as the tough but caring owner and manager of the struggling burlesque club.
  • B. Tess
    Tess is a 1979 period drama film directed by Roman Polanski, adapted from Thomas Hardy’s novel "Tess of the d'Urbervilles."
  • C. Far from the Madding Crowd
    Far from the Madding Crowd is an 1874 novel by Thomas Hardy that follows the romantic and social entanglements of the independent Bathsheba Everdene in rural Victorian England.
  • D. The Farmer’s Daughter
    The Farmer’s Daughter is a 1947 American romantic comedy film starring Loretta Young as a Swedish-American farm girl who becomes involved in politics.
  • E. Ethan Frome
    Ethan Frome is a 1993 American drama film directed by John Madden, adapted from Edith Wharton's novel about a tragic love triangle in a bleak New England setting.
  • 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_69bd445edb3881909b93b34d260717fc completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79073a54819080cd1e8de6fe906a completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed92b3ab48190900cf5c246dba433 completed March 21, 2026, 5:45 p.m.
NEDg Description generation batch_69beda3bfee08190a6e1d8b06739cade completed March 21, 2026, 5:49 p.m.
NED2 Entity disambiguation (via description) batch_69beda93175481908c79010c7fe6897e completed March 21, 2026, 5:51 p.m.
Created at: March 20, 2026, 1:44 p.m.