Triple
T12500620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isla Fisher |
E298809
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Isla Fisher |
E298809
|
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: Isla Fisher | Statement: [Isla Fisher, name, Isla Fisher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isla Fisher Context triple: [Isla Fisher, name, Isla Fisher]
-
A.
Isla Fisher
chosen
Isla Fisher is an Australian actress and author known for her comedic roles in films such as "Wedding Crashers," "Confessions of a Shopaholic," and "Now You See Me."
-
B.
Leslie Mann
Leslie Mann is an American actress known for her comedic and dramatic roles in films such as "The 40-Year-Old Virgin," "Knocked Up," and "This Is 40."
-
C.
Owen Wilson
Owen Wilson is an American actor and screenwriter known for his laid-back charm and roles in popular comedies and adventure films such as "Wedding Crashers," "Zoolander," and "Midnight in Paris."
-
D.
Anna Kendrick
Anna Kendrick is an American actress and singer known for her versatile performances in films such as "Pitch Perfect," "Up in the Air," and the musical fantasy "Into the Woods."
-
E.
Mila Kunis
Mila Kunis is an American actress known for her roles in films like "Black Swan" and "Forgetting Sarah Marshall" and for voicing Meg Griffin on the animated series "Family Guy."
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfbb2a48190a231b02cfa990565 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb38e048190bbc96244b71953b6 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.