Triple
T984797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Like Crazy |
E21254
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Felicity Jones |
E103015
|
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: Felicity Jones | Statement: [Like Crazy, starring, Felicity Jones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Felicity Jones Context triple: [Like Crazy, starring, Felicity Jones]
-
A.
Felicity Jones
chosen
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."
-
B.
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."
-
C.
Ruby Rose
Ruby Rose is an Australian model, DJ, and actress known for her androgynous style and roles in action films and television series such as "Orange Is the New Black."
-
D.
Emilia Clarke
Emilia Clarke is an English actress best known for her role as Daenerys Targaryen in the television series "Game of Thrones."
-
E.
Katherine Hoult
Katherine Hoult is known as the spouse of Richard Mather.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac537d788c81908d239f102626bdd6 |
completed | March 7, 2026, 4:34 p.m. |
Created at: March 1, 2026, 7:41 p.m.