Triple
T18099248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nostromo |
E433171
|
entity |
| Predicate | setDesignBy |
P184
|
FINISHED |
| Object | Chris Foss |
—
|
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: Chris Foss | Statement: [Nostromo, setDesignBy, Chris Foss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Foss Context triple: [Nostromo, setDesignBy, Chris Foss]
-
A.
Chris Foss
chosen
Chris Foss is a British artist renowned for his highly detailed, vividly colored science fiction book and magazine cover illustrations, especially of futuristic spacecraft and machinery.
-
B.
Michael Fagan
Michael Fagan is a British man best known for breaking into Buckingham Palace and entering Queen Elizabeth II’s bedroom in 1982, one of the most notorious royal security breaches in modern history.
-
C.
Frank Mauro
Frank Mauro is a musician known for being a member of the influential New York punk band Richard Hell and the Voidoids.
-
D.
Robert Clohessy
Robert Clohessy is an American actor best known for his recurring roles on television dramas, including his portrayal of police officers on series such as Blue Bloods and Oz.
-
E.
Mike Rudell
Mike Rudell is a fictional character from the dark comedy film "Mini's First Time."
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb521448190b97d2b2aa7e4d7e6 |
completed | April 19, 2026, 1:50 p.m. |
Created at: April 10, 2026, 10:27 a.m.