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.