Triple

T11243091
Position Surface form Disambiguated ID Type / Status
Subject From Hand to Mouth E266123 entity
Predicate hasCastMember P2308 FINISHED
Object Mark Jones
Mark Jones is an actor known for his role in the film "From Hand to Mouth."
E913521 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: Mark Jones | Statement: [From Hand to Mouth, hasCastMember, Mark Jones]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Jones
Context triple: [From Hand to Mouth, hasCastMember, Mark Jones]
  • A. Mark Jones
    Mark Jones was an English footballer for Manchester United and England who died in the 1958 Munich air disaster.
  • B. Matt Jones
    Matt Jones is an American actor and comedian best known for his roles in television series like "Breaking Bad" and for his extensive voice work in animated shows and video games.
  • C. Matt Jones
    Matt Jones is a British musician best known as a former member of the rock band Beady Eye, formed by ex-Oasis members.
  • D. Ken Jones
    Ken Jones was a prominent African American LGBTQ activist and community organizer known for his work in San Francisco’s gay rights and HIV/AIDS movements.
  • E. Peter Jones
    Peter Jones is a British entrepreneur, investor, and television personality best known as a long-standing "dragon" on the BBC series Dragons' Den.
  • 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: Mark Jones
Triple: [From Hand to Mouth, hasCastMember, Mark Jones]
Generated description
Mark Jones is an actor known for his role in the film "From Hand to Mouth."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mark Jones
Target entity description: Mark Jones is an actor known for his role in the film "From Hand to Mouth."
  • A. Mark Jones
    Mark Jones was an English footballer for Manchester United and England who died in the 1958 Munich air disaster.
  • B. Matt Jones
    Matt Jones is an American actor and comedian best known for his roles in television series like "Breaking Bad" and for his extensive voice work in animated shows and video games.
  • C. Matt Jones
    Matt Jones is a British musician best known as a former member of the rock band Beady Eye, formed by ex-Oasis members.
  • D. Ken Jones
    Ken Jones was a prominent African American LGBTQ activist and community organizer known for his work in San Francisco’s gay rights and HIV/AIDS movements.
  • E. Peter Jones
    Peter Jones is a British entrepreneur, investor, and television personality best known as a long-standing "dragon" on the BBC series Dragons' Den.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e91b0b808190bc38008bb344d180 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad849f70819098a7056fbc4831ff completed April 19, 2026, 10:25 a.m.
NEDg Description generation batch_69e4b12eee348190bee6c84587e4955d completed April 19, 2026, 10:40 a.m.
NED2 Entity disambiguation (via description) batch_69e4be2bb8c88190a21773b0c43b6b99 completed April 19, 2026, 11:36 a.m.
Created at: April 8, 2026, 9:30 p.m.