Triple
T12318665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saw IV |
E293670
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Scott Patterson |
E607515
|
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: Scott Patterson | Statement: [Saw IV, stars, Scott Patterson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Patterson Context triple: [Saw IV, stars, Scott Patterson]
-
A.
Scott Patterson
chosen
Scott Patterson is an American actor best known for playing diner owner Luke Danes on the television series "Gilmore Girls."
-
B.
Steven Patterson
Steven Patterson is a relatively obscure individual whose primary distinction is sharing the surname associated with the Patterson family name.
-
C.
Shawn Patterson
Shawn Patterson is an American composer and songwriter best known for his work on film and television scores, including the hit song "Everything Is Awesome" from The Lego Movie.
-
D.
Dennis Patterson
Dennis Patterson is a central character in the British television drama-comedy "Auf Wiedersehen, Pet," known as the responsible, level-headed leader among a group of itinerant construction workers.
-
E.
Sean McKittrick
Sean McKittrick is an American film producer known for his work on acclaimed and genre-defining films such as "BlacKkKlansman," "Get Out," and "Donnie Darko."
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4ab1b88190979a8403a430a17c |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63eefad508190be266c776525a7cc |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:53 p.m.