Triple
T10494026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snake Eyes |
E247488
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Carla Gugino |
E71289
|
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: Carla Gugino | Statement: [Snake Eyes, starring, Carla Gugino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carla Gugino Context triple: [Snake Eyes, starring, Carla Gugino]
-
A.
Carla Gugino
chosen
Carla Gugino is an American actress known for her versatile film and television roles, including prominent performances in projects like "Spy Kids," "Sin City," and "The Haunting of Hill House."
-
B.
Karen Rodriguez
Karen Rodriguez is an actress known for her role in the television series "Swarm."
-
C.
Gina Torres
Gina Torres is an American actress known for her roles in television series such as "Suits," "Firefly," and "Hannibal."
-
D.
Melissa Cobb
Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
-
E.
Linda Cardellini
Linda Cardellini is an American actress known for her versatile roles in film and television, including prominent performances in "Freaks and Geeks," "ER," "Bloodline," and as Laura Barton in 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097fe2bc81909d66ce43f3533284 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9882acd348190ae3ab2f17c834aef |
completed | April 10, 2026, 11:30 p.m. |
Created at: April 6, 2026, 12:24 p.m.