Triple
T6015651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Weller |
E133943
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Peter Weller |
E133943
|
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: Peter Weller | Statement: [Peter Weller, name, Peter Weller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Weller Context triple: [Peter Weller, name, Peter Weller]
-
A.
Peter Weller
chosen
Peter Weller is an American actor and director best known for his iconic role as the title character in the "RoboCop" films and for numerous appearances in science fiction and television.
-
B.
Tim Matheson
Tim Matheson is an American actor and director best known for his roles in films like "National Lampoon's Animal House" and numerous television series.
-
C.
Michael Biehn
Michael Biehn is an American actor best known for his roles in science fiction and action films such as The Terminator, Aliens, and The Abyss.
-
D.
Fred Ward
Fred Ward was an American character actor known for his rugged, everyman roles in films such as "Tremors," "The Right Stuff," and "Short Cuts."
-
E.
Matthew Modine
Matthew Modine is an American actor best known for his roles in films like "Full Metal Jacket" and the series "Stranger Things."
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f80ec108190ae9711727debb061 |
completed | March 22, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1136a4720819092bf2c6a9101c71b |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:06 p.m.