Triple
T17607200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deadfall |
E428863
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Michael Biehn |
—
|
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: Michael Biehn | Statement: [Deadfall, starring, Michael Biehn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Biehn Context triple: [Deadfall, starring, Michael Biehn]
-
A.
Michael Biehn
chosen
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.
-
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.
Chris Hargensen
Chris Hargensen is a central antagonist in Stephen King’s novel "Carrie," known as a cruel high school bully whose actions help trigger the story’s catastrophic climax.
-
D.
Peter Weller
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.
-
E.
Lance Henriksen
Lance Henriksen is an American character actor best known for his intense performances in science fiction and horror films such as the Alien franchise and the TV series Millennium.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4ccef08190aeaa88670364bd74 |
completed | April 19, 2026, 5:46 a.m. |
Created at: April 10, 2026, 5:51 a.m.