Triple
T16086421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy Pond |
E390239
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Karen Gillan |
E256907
|
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: Karen Gillan | Statement: [Amy Pond, portrayedBy, Karen Gillan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Gillan Context triple: [Amy Pond, portrayedBy, Karen Gillan]
-
A.
Karen Gillan
chosen
Karen Gillan is a Scottish actress and filmmaker best known for her roles as Nebula in the Marvel Cinematic Universe and Amy Pond in the television series Doctor Who.
-
B.
Kate Fisher
Kate Fisher is the mother of American singer and actor Eddie Fisher.
-
C.
Felicity Jones
Felicity Jones is an English actress known for her roles in films such as "The Theory of Everything" and "Rogue One: A Star Wars Story."
-
D.
Tamsin Egerton
Tamsin Egerton is an English actress and model known for roles in films such as "St Trinian's," "Keeping Mum," and "The Look of Love."
-
E.
Laura Bailey
Laura Bailey is an acclaimed American voice actress known for her prominent roles in video games and animation, including award-winning performances in major titles.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1844f95508190a06dad0ccc9b6191 |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff79a96d08190af69cbb18037f66e |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 4:59 a.m.