Triple
T8408611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell Metty |
E198564
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Metty
Metty is the surname of Russell Metty, an American cinematographer known for his work on classic Hollywood films such as "Spartacus" and "Touch of Evil."
|
E731416
|
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: Metty | Statement: [Russell Metty, familyName, Metty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metty Context triple: [Russell Metty, familyName, Metty]
-
A.
Capucine
Capucine was a French fashion model and film actress best known for her elegant screen presence in 1960s comedies and dramas, including roles in films like The Pink Panther.
-
B.
Mariette
Mariette is a French feminine given name, commonly used as a diminutive or affectionate form of Marie.
-
C.
Saide
Saide is a given name that serves as an alternative spelling of the more common name Sadie.
-
D.
Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
-
E.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
- 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: Metty Triple: [Russell Metty, familyName, Metty]
Generated description
Metty is the surname of Russell Metty, an American cinematographer known for his work on classic Hollywood films such as "Spartacus" and "Touch of Evil."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Metty Target entity description: Metty is the surname of Russell Metty, an American cinematographer known for his work on classic Hollywood films such as "Spartacus" and "Touch of Evil."
-
A.
Capucine
Capucine was a French fashion model and film actress best known for her elegant screen presence in 1960s comedies and dramas, including roles in films like The Pink Panther.
-
B.
Mariette
Mariette is a French feminine given name, commonly used as a diminutive or affectionate form of Marie.
-
C.
Saide
Saide is a given name that serves as an alternative spelling of the more common name Sadie.
-
D.
Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
-
E.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8315a8a8819097f6da11b909b527 |
completed | March 31, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce030dccf08190a70c0abf0bdcf244 |
completed | April 2, 2026, 5:47 a.m. |
| NEDg | Description generation | batch_69ce07808098819087e896b87320aefd |
completed | April 2, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce08759e1c81909c96caf3b571e1ca |
completed | April 2, 2026, 6:11 a.m. |
Created at: March 30, 2026, 6:05 p.m.