Triple
T3673295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantastic Mr. Fox |
E77928
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Jeremy Dawson |
E240276
|
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: Jeremy Dawson | Statement: [Fantastic Mr. Fox, producer, Jeremy Dawson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeremy Dawson Context triple: [Fantastic Mr. Fox, producer, Jeremy Dawson]
-
A.
Jeremy Dawson
chosen
Jeremy Dawson is a film producer best known for his work on Wes Anderson’s movies, including the acclaimed feature "The Grand Budapest Hotel."
-
B.
John Dawson
John Dawson is a fictional character named John Dawson who appears in the work featuring the character Dawn.
-
C.
John Dawson
John Dawson was a pioneering American plasma physicist renowned for his foundational contributions to plasma theory and fusion research.
-
D.
Alexander Haddow
Alexander Haddow was a Scottish epidemiologist and virologist noted for his pioneering research on insect-borne viruses, particularly in Africa.
-
E.
Graydon Hoare
Graydon Hoare is a Canadian software developer best known as the original creator of the Rust programming language.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42f82548190b4d5f0fe7250decb |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48854a2308190ba6a9fc39929b35c |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.