Triple
T13665785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 47 Meters Down: Uncaged |
E327115
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Mark Silk
Mark Silk is a cinematographer known for his work on feature films, including the shark thriller "47 Meters Down: Uncaged."
|
E1053526
|
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 Silk | Statement: [47 Meters Down: Uncaged, cinematographyBy, Mark Silk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Silk Context triple: [47 Meters Down: Uncaged, cinematographyBy, Mark Silk]
-
A.
Scott Rothkopf
Scott Rothkopf is an American art curator and museum director known for his leadership and influential exhibitions at the Whitney Museum of American Art.
-
B.
Adam S. Posen
Adam S. Posen is an American economist known for his work on monetary policy and international economics, and for leading the Peterson Institute for International Economics.
-
C.
Mark Naimark
Mark Naimark was a Soviet mathematician known for his influential work in functional analysis and operator algebras.
-
D.
Vik Rubenfeld
Vik Rubenfeld is a television writer and producer best known for creating the fantasy-drama series "Early Edition."
-
E.
Stephen Cohen
Stephen Cohen is a technology entrepreneur best known as a co-founder of the data analytics company Palantir Technologies.
- 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 Silk Triple: [47 Meters Down: Uncaged, cinematographyBy, Mark Silk]
Generated description
Mark Silk is a cinematographer known for his work on feature films, including the shark thriller "47 Meters Down: Uncaged."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Silk Target entity description: Mark Silk is a cinematographer known for his work on feature films, including the shark thriller "47 Meters Down: Uncaged."
-
A.
Scott Rothkopf
Scott Rothkopf is an American art curator and museum director known for his leadership and influential exhibitions at the Whitney Museum of American Art.
-
B.
Adam S. Posen
Adam S. Posen is an American economist known for his work on monetary policy and international economics, and for leading the Peterson Institute for International Economics.
-
C.
Mark Naimark
Mark Naimark was a Soviet mathematician known for his influential work in functional analysis and operator algebras.
-
D.
Vik Rubenfeld
Vik Rubenfeld is a television writer and producer best known for creating the fantasy-drama series "Early Edition."
-
E.
Stephen Cohen
Stephen Cohen is a technology entrepreneur best known as a co-founder of the data analytics company Palantir Technologies.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc623fcc88190bbad97541c040b7a |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b0ac4c88190ab6f753c6847eb6e |
completed | May 3, 2026, 5:51 p.m. |
| NEDg | Description generation | batch_69f78cdf1a74819087b0370060ddfa99 |
completed | May 3, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78e00007c81909007a751fd4625c2 |
completed | May 3, 2026, 6:03 p.m. |
Created at: April 9, 2026, 9:52 p.m.