Triple
T8441263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thor: The Dark World |
E199355
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Tom Hiddleston |
E85997
|
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: Tom Hiddleston | Statement: [Thor: The Dark World, stars, Tom Hiddleston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Hiddleston Context triple: [Thor: The Dark World, stars, Tom Hiddleston]
-
A.
Tom Hiddleston
chosen
Tom Hiddleston is an English actor best known for his charismatic portrayal of Loki in the Marvel Cinematic Universe and for acclaimed performances in film, television, and theatre.
-
B.
James Norman Hiddleston
James Norman Hiddleston is the father of British actor Tom Hiddleston and is known as a Scottish-born chemist and former managing director in the pharmaceutical industry.
-
C.
Sarah Hiddleston
Sarah Hiddleston is best known as the sister of British actor Tom Hiddleston.
-
D.
Chris Hemsworth
Chris Hemsworth is an Australian actor best known for portraying the Marvel superhero Thor in the Marvel Cinematic Universe films.
-
E.
Sebastian Stan
Sebastian Stan is a Romanian-American actor best known for playing Bucky Barnes/The Winter Soldier in the Marvel Cinematic Universe and appearing in films such as "I, Tonya" and "Pam & Tommy."
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe138a94081908e306d22aaa39b24 |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d9ab3a88190ada7741cf054fc1b |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:08 p.m.