Triple
T12901389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B’Elanna Torres |
E308619
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Roxann Dawson |
E778105
|
NE FINISHED |
How this triple was built (2 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: Roxann Dawson | Statement: [B’Elanna Torres, portrayedBy, Roxann Dawson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roxann Dawson Context triple: [B’Elanna Torres, portrayedBy, Roxann Dawson]
-
A.
Roxann Dawson
chosen
Roxann Dawson is an American actress and director best known for playing Chief Engineer B'Elanna Torres on the television series Star Trek: Voyager.
-
B.
Kate Mara
Kate Mara is an American actress known for her roles in films like "The Martian" and "Brokeback Mountain" and TV series such as "House of Cards."
-
C.
Julie Benz
Julie Benz is an American actress best known for her roles on television series such as "Buffy the Vampire Slayer," "Angel," and "Dexter."
-
D.
Charena Swann
Charena Swann is the wife of former NFL star and Pro Football Hall of Famer Lynn Swann.
-
E.
Zoe Saldana
Zoe Saldana is an American actress known for her prominent roles in major science fiction and fantasy franchises, including Star Trek, Avatar, and the Marvel Cinematic Universe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97180ee708190b60a3e58c42f764f |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d5ef4ba8819099335d155feb01d9 |
completed | May 3, 2026, 4:58 a.m. |
Created at: April 9, 2026, 5:40 p.m.