Triple
T6538088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noah Taylor |
E168216
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Noah Taylor |
E168216
|
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: Noah Taylor | Statement: [Noah Taylor, name, Noah Taylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noah Taylor Context triple: [Noah Taylor, name, Noah Taylor]
-
A.
Noah Taylor
chosen
Noah Taylor is an Australian actor known for his character roles in films such as "Shine," "Almost Famous," and "Game of Thrones."
-
B.
Noah Hutton
Noah Hutton is an American filmmaker and documentarian known for his work on science-focused and socially conscious films.
-
C.
Noah Timmins
Noah Timmins was a prominent Canadian mining financier and pioneer whose investments helped develop major gold mining operations in northern Ontario in the early 20th century.
-
D.
Noah Huntley
Noah Huntley is a British actor and former model known for roles in films such as "28 Days Later," "Snow White and the Huntsman," and "The Chronicles of Narnia: The Lion, the Witch and the Wardrobe."
-
E.
Noah Segan
Noah Segan is an American actor best known for his frequent collaborations with director Rian Johnson, including roles in films like "Looper" and "Knives Out."
- 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_69c68a51564081909e93aee0dbd9cca3 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6add4b7f881909e485325c353f51c |
completed | March 27, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d5389fac8190bbad946de79d6086 |
completed | March 27, 2026, 7:06 p.m. |
Created at: March 27, 2026, 1:49 p.m.