Triple
T14640150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beatriz at Dinner |
E343700
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Shannon
Shannon is a character in the satirical drama film "Beatriz at Dinner," serving as one of the guests whose interactions highlight the movie’s themes of class, privilege, and cultural conflict.
|
E1306223
|
NE FINISHED |
How this triple was built (3 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.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shannon Context triple: [Beatriz at Dinner, character, Shannon]
-
A.
Shannon
Shannon is a common Irish surname that originates from the River Shannon and is borne by numerous notable individuals, including mathematician and information theorist Claude Shannon.
-
B.
Shannon
Shannon is a small rural town in the Manawatū-Whanganui region of New Zealand’s North Island.
-
C.
Shannon
Shannon is a small municipality in Quebec, Canada, known for its proximity to Canadian Forces Base Valcartier and its largely bilingual, predominantly anglophone community.
-
D.
Shannon
Shannon is a modern planned town in County Clare, Ireland, best known for its proximity to Shannon Airport and its role as an industrial and commercial hub in the Mid-West region.
-
E.
Shannons
Shannons is an Australian insurance company best known for providing specialist car and motorcycle insurance, particularly for motoring enthusiasts and classic vehicle owners.
- 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: Shannon Triple: [Beatriz at Dinner, character, Shannon]
Generated description
Shannon is a character in the satirical drama film "Beatriz at Dinner," serving as one of the guests whose interactions highlight the movie’s themes of class, privilege, and cultural conflict.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shannon Target entity description: Shannon is a character in the satirical drama film "Beatriz at Dinner," serving as one of the guests whose interactions highlight the movie’s themes of class, privilege, and cultural conflict.
-
A.
Shannon
Shannon is a common Irish surname that originates from the River Shannon and is borne by numerous notable individuals, including mathematician and information theorist Claude Shannon.
-
B.
Shannon
Shannon is a small rural town in the Manawatū-Whanganui region of New Zealand’s North Island.
-
C.
Shannon
Shannon is a small municipality in Quebec, Canada, known for its proximity to Canadian Forces Base Valcartier and its largely bilingual, predominantly anglophone community.
-
D.
Shannon
Shannon is a modern planned town in County Clare, Ireland, best known for its proximity to Shannon Airport and its role as an industrial and commercial hub in the Mid-West region.
-
E.
Shannons
Shannons is an Australian insurance company best known for providing specialist car and motorcycle insurance, particularly for motoring enthusiasts and classic vehicle owners.
- F. None of above. chosen
Provenance (4 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a037c1ca5408190ba46c0ce5515062a |
completed | May 12, 2026, 7:14 p.m. |
| NEDg | Description generation | batch_6a037ca6f5888190b0ed34777aae862f |
completed | May 12, 2026, 7:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a037d319be48190b01a1b8d1f239078 |
completed | May 12, 2026, 7:19 p.m. |
Created at: April 10, 2026, 1:26 a.m.