Triple
T9506374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Goldwyn |
E229279
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Goldwyn
Goldwyn is a notable American surname most famously associated with film producer Samuel Goldwyn and his entertainment-industry family.
|
E803308
|
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: Goldwyn | Statement: [Tony Goldwyn, familyName, Goldwyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goldwyn Context triple: [Tony Goldwyn, familyName, Goldwyn]
-
A.
Melvyn
Melvyn is the surname of Sybylla Melvyn, the spirited young protagonist of Miles Franklin’s classic Australian novel "My Brilliant Career."
-
B.
Lasky
Lasky is a surname most notably associated with Jesse L. Lasky, a pioneering American film producer and co-founder of Paramount Pictures.
-
C.
Orson
Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
-
D.
Guillermin
Guillermin is a French-origin surname most notably associated with British film director John Guillermin, known for works such as "The Towering Inferno" and the 1976 remake of "King Kong."
-
E.
Modjeski
Modjeski is the surname of Ralph Modjeski, a prominent Polish-American civil engineer renowned for designing major bridges in the United States.
- 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: Goldwyn Triple: [Tony Goldwyn, familyName, Goldwyn]
Generated description
Goldwyn is a notable American surname most famously associated with film producer Samuel Goldwyn and his entertainment-industry family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Goldwyn Target entity description: Goldwyn is a notable American surname most famously associated with film producer Samuel Goldwyn and his entertainment-industry family.
-
A.
Melvyn
Melvyn is the surname of Sybylla Melvyn, the spirited young protagonist of Miles Franklin’s classic Australian novel "My Brilliant Career."
-
B.
Lasky
Lasky is a surname most notably associated with Jesse L. Lasky, a pioneering American film producer and co-founder of Paramount Pictures.
-
C.
Orson
Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
-
D.
Guillermin
Guillermin is a French-origin surname most notably associated with British film director John Guillermin, known for works such as "The Towering Inferno" and the 1976 remake of "King Kong."
-
E.
Modjeski
Modjeski is the surname of Ralph Modjeski, a prominent Polish-American civil engineer renowned for designing major bridges in the United States.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9852b7e48190a8f69cbde10d2858 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a1de2d88190a6a10379d2297510 |
completed | April 4, 2026, 4:19 p.m. |
| NEDg | Description generation | batch_69d13ad61c6c8190baad9c4f166ca1ae |
completed | April 4, 2026, 4:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d13b4a7b808190badf83c88fb06b82 |
completed | April 4, 2026, 4:24 p.m. |
Created at: March 30, 2026, 7:57 p.m.