Triple

T6463748
Position Surface form Disambiguated ID Type / Status
Subject Never Die Alone E142181 entity
Predicate hasCharacter P2308 FINISHED
Object Paul
Paul is a character in the crime drama film "Never Die Alone," which follows the violent, intertwined lives of drug dealers and those around them.
 E594177 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: Paul | Statement: [Never Die Alone, hasCharacter, Paul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paul
Context triple: [Never Die Alone, hasCharacter, Paul]
  • A. Paul
    Paul is a laid-back, charming sperm donor whose unexpected involvement with his biological children disrupts a lesbian couple’s family dynamic in the film "The Kids Are All Right."
  • B. Paul
    Paul is a masculine given name of Latin origin, widely used in many Western and Christian-influenced cultures.
  • C. Paul
    Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
  • D. Paul
    Paul is a 2011 sci-fi comedy film about two British geeks who encounter a wisecracking alien during a road trip across the United States.
  • E. Paul
    Paul is a village and civil parish in Cornwall, England, known for its historic church and coastal setting near Penzance.
  • 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: Paul
Triple: [Never Die Alone, hasCharacter, Paul]
Generated description
Paul is a character in the crime drama film "Never Die Alone," which follows the violent, intertwined lives of drug dealers and those around them.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paul
Target entity description: Paul is a character in the crime drama film "Never Die Alone," which follows the violent, intertwined lives of drug dealers and those around them.
  • A. Paul
    Paul is a masculine given name of Latin origin, widely used in many Western and Christian-influenced cultures.
  • B. Paul
    Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
  • C. Paul
    Paul is a laid-back, charming sperm donor whose unexpected involvement with his biological children disrupts a lesbian couple’s family dynamic in the film "The Kids Are All Right."
  • D. Paul
    Paul is a 2011 sci-fi comedy film about two British geeks who encounter a wisecracking alien during a road trip across the United States.
  • E. Paul
    Paul is a village and civil parish in Cornwall, England, known for its historic church and coastal setting near Penzance.
  • 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069f9b58081909412b9da753b9285 completed March 22, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64be78ae48190b38390ed245694fb completed March 27, 2026, 9:20 a.m.
NEDg Description generation batch_69c64cd369048190bc0702592083a909 completed March 27, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_69c64d911a1881908b280636365a4858 completed March 27, 2026, 9:27 a.m.
Created at: March 22, 2026, 4:49 p.m.