Triple

T56552
Position Surface form Disambiguated ID Type / Status
Subject Seth MacFarlane E1118 entity
Predicate notableWork P4 FINISHED
Object Ted 2
Ted 2 is a 2015 American comedy film and sequel to Ted, following the foul-mouthed talking teddy bear as he fights for his civil rights alongside his best friend.
E5048 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: Ted 2 | Statement: [Seth MacFarlane, notableWork, Ted 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ted 2
Context triple: [Seth MacFarlane, notableWork, Ted 2]
  • A. TNT
    TNT is an American cable television network known for airing sports, movies, and original drama programming.
  • B. Clementine
    Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
  • C. TOTEM
    TOTEM is a high-energy physics experiment at CERN’s Large Hadron Collider that precisely measures proton–proton scattering and total cross sections.
  • D. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • E. Blitz
    The Blitz was the sustained German bombing campaign against the United Kingdom, particularly London, during 1940–1941 in World War II.
  • 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: Ted 2
Triple: [Seth MacFarlane, notableWork, Ted 2]
Generated description
Ted 2 is a 2015 American comedy film and sequel to Ted, following the foul-mouthed talking teddy bear as he fights for his civil rights alongside his best friend.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ted 2
Target entity description: Ted 2 is a 2015 American comedy film and sequel to Ted, following the foul-mouthed talking teddy bear as he fights for his civil rights alongside his best friend.
  • A. TNT
    TNT is an American cable television network known for airing sports, movies, and original drama programming.
  • B. Clementine
    Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
  • C. TOTEM
    TOTEM is a high-energy physics experiment at CERN’s Large Hadron Collider that precisely measures proton–proton scattering and total cross sections.
  • D. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • E. Autoport
    Autoport is a specialized automotive terminal within the Port of Boston used for handling, storing, and processing imported and exported vehicles.
  • 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_69a248adc5b48190aa8db9fb092fb28a completed Feb. 28, 2026, 1:45 a.m.
NER Named-entity recognition batch_69a24b07f4a881909e32115e84da02a3 completed Feb. 28, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2554a9e70819099ab14df3da5e403 completed Feb. 28, 2026, 2:39 a.m.
NEDg Description generation batch_69a2569d3d008190ad1546d18ba30375 completed Feb. 28, 2026, 2:44 a.m.
NED2 Entity disambiguation (via description) batch_69a2573414808190bbab27e1f48479a5 completed Feb. 28, 2026, 2:47 a.m.
Created at: Feb. 28, 2026, 1:50 a.m.