Triple
T13911611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | xXx: Return of Xander Cage |
E334510
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Serena Unger
Serena Unger is a fearless, highly skilled operative and leader of an elite team in the action film "xXx: Return of Xander Cage," portrayed by Deepika Padukone.
|
E1067226
|
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: Serena Unger | Statement: [xXx: Return of Xander Cage, character, Serena Unger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serena Unger Context triple: [xXx: Return of Xander Cage, character, Serena Unger]
-
A.
Serena Evans
Serena Evans is a British actress best known for her role in the BBC sitcom "The Thin Blue Line."
-
B.
Serena Brown
Serena Brown is the daughter of Bob Brown.
-
C.
Serena Southerlyn
Serena Southerlyn is a fictional Assistant District Attorney on the long-running television series "Law & Order," known for her idealism and strong moral convictions in prosecuting cases.
-
D.
Angela Greene
Angela Greene was an American film and television actress active in the mid-20th century, known for her supporting roles in various Hollywood productions.
-
E.
Serena Powers
Serena Powers is a relatively obscure individual whose specific public achievements or background are not widely documented.
- 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: Serena Unger Triple: [xXx: Return of Xander Cage, character, Serena Unger]
Generated description
Serena Unger is a fearless, highly skilled operative and leader of an elite team in the action film "xXx: Return of Xander Cage," portrayed by Deepika Padukone.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Serena Unger Target entity description: Serena Unger is a fearless, highly skilled operative and leader of an elite team in the action film "xXx: Return of Xander Cage," portrayed by Deepika Padukone.
-
A.
Serena Evans
Serena Evans is a British actress best known for her role in the BBC sitcom "The Thin Blue Line."
-
B.
Serena Brown
Serena Brown is the daughter of Bob Brown.
-
C.
Serena Southerlyn
Serena Southerlyn is a fictional Assistant District Attorney on the long-running television series "Law & Order," known for her idealism and strong moral convictions in prosecuting cases.
-
D.
Angela Greene
Angela Greene was an American film and television actress active in the mid-20th century, known for her supporting roles in various Hollywood productions.
-
E.
Serena Powers
Serena Powers is a relatively obscure individual whose specific public achievements or background are not widely documented.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2723461881908376b5509ee0d530 |
completed | April 14, 2026, 11:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c72879e48190ac01d0a2023b098c |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c7b9e4888190822501d439df142a |
completed | May 3, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c83e31d4819094209406fc99456a |
completed | May 3, 2026, 10:12 p.m. |
Created at: April 9, 2026, 10:16 p.m.