Triple
T7483832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mighty Med |
E176828
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Paris Berelc
Paris Berelc is an American actress and model best known for her roles in Disney XD and Netflix series, including action and comedy projects aimed at younger audiences.
|
E667038
|
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: Paris Berelc | Statement: [Mighty Med, stars, Paris Berelc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris Berelc Context triple: [Mighty Med, stars, Paris Berelc]
-
A.
Jules Sitruk
Jules Sitruk is a French actor known for his early roles in films such as "Monsieur Batignole" and "Son of Rambow."
-
B.
Marcel Ruiz
Marcel Ruiz is a Puerto Rican-American actor best known for his role as Alex Alvarez on the Netflix sitcom "One Day at a Time."
-
C.
Peter Biziou
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
-
D.
Gilbert Rozon
Gilbert Rozon is a Canadian entertainment producer best known as the controversial founder of the international comedy festival Just for Laughs.
-
E.
Gilbert Trigano
Gilbert Trigano was a French entrepreneur best known for transforming Club Med into a pioneering global chain of all-inclusive holiday resorts.
- 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: Paris Berelc Triple: [Mighty Med, stars, Paris Berelc]
Generated description
Paris Berelc is an American actress and model best known for her roles in Disney XD and Netflix series, including action and comedy projects aimed at younger audiences.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paris Berelc Target entity description: Paris Berelc is an American actress and model best known for her roles in Disney XD and Netflix series, including action and comedy projects aimed at younger audiences.
-
A.
Jules Sitruk
Jules Sitruk is a French actor known for his early roles in films such as "Monsieur Batignole" and "Son of Rambow."
-
B.
Marcel Ruiz
Marcel Ruiz is a Puerto Rican-American actor best known for his role as Alex Alvarez on the Netflix sitcom "One Day at a Time."
-
C.
Peter Biziou
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
-
D.
Gilbert Rozon
Gilbert Rozon is a Canadian entertainment producer best known as the controversial founder of the international comedy festival Just for Laughs.
-
E.
Gilbert Trigano
Gilbert Trigano was a French entrepreneur best known for transforming Club Med into a pioneering global chain of all-inclusive holiday resorts.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f53923e4819081bf79ed962a971c |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8349d83cc8190af98c3212e28e913 |
completed | March 28, 2026, 8:05 p.m. |
| NEDg | Description generation | batch_69c835916e948190ad5789e4611f8842 |
completed | March 28, 2026, 8:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83635c7888190834f02e7ea0f1ab5 |
completed | March 28, 2026, 8:12 p.m. |
Created at: March 27, 2026, 3:42 p.m.