Triple
T20167176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cloverfield Paradox |
E491851
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Doug J. Hannah |
—
|
NE NERFINISHED |
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: Doug J. Hannah | Statement: [The Cloverfield Paradox, editor, Doug J. Hannah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doug J. Hannah Context triple: [The Cloverfield Paradox, editor, Doug J. Hannah]
-
A.
Doug J. Hannah
chosen
Doug J. Hannah is a film editor best known for his work on the science fiction thriller "The Cloverfield Paradox."
-
B.
Don Hannah
Don Hannah is a Canadian playwright and novelist known for works that often explore life in Atlantic Canada.
-
C.
Joe Hahn
Joe Hahn is an American musician and DJ best known as the turntablist and sampler for the rock band Linkin Park.
-
D.
Ed Hartnett
Ed Hartnett is an American software developer best known as the creator and primary maintainer of the NetCDF-4 library widely used in scientific computing and data analysis.
-
E.
Bill Harrigan
Bill Harrigan is a former Australian rugby league referee widely regarded as one of the sport’s most prominent and experienced officials.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66844e49081909b7e9ec2b65cc61d |
completed | April 20, 2026, 5:54 p.m. |
Created at: April 11, 2026, 11:35 p.m.