Triple
T1181717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thompson |
E25151
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Tessa Thompson |
E39245
|
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: Tessa Thompson | Statement: [Thompson, hasNotableBearer, Tessa Thompson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Thompson Context triple: [Thompson, hasNotableBearer, Tessa Thompson]
-
A.
Tessa Thompson
chosen
Tessa Thompson is an American actress known for her versatile performances in film and television, including prominent roles in projects like "Creed," "Thor: Ragnarok," and "Westworld."
-
B.
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."
-
C.
Maggie Siff
Maggie Siff is an American actress best known for her television roles in series such as Mad Men, Sons of Anarchy, and Billions.
-
D.
Rooney Mara
Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
-
E.
Alicia Vikander
Alicia Vikander is a Swedish actress known for her acclaimed performances in films such as "Ex Machina," "The Danish Girl," and "Tomb Raider."
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd347d4481909e9094463011289d |
completed | March 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f21547c81909cf23c454436e839 |
completed | March 7, 2026, 6:32 p.m. |
Created at: March 1, 2026, 7:45 p.m.