Triple
T9790113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bleed for This |
E237584
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ted Levine |
E65187
|
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: Ted Levine | Statement: [Bleed for This, starring, Ted Levine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Levine Context triple: [Bleed for This, starring, Ted Levine]
-
A.
Ted Levine
chosen
Ted Levine is an American character actor best known for his chilling portrayal of serial killer Buffalo Bill in the film "The Silence of the Lambs."
-
B.
Brian Reynolds
Brian Reynolds is a technology entrepreneur best known as a founder of the enterprise software company Micro Focus.
-
C.
Neil Druckmann
Neil Druckmann is a video game writer, director, and executive at Naughty Dog best known for co-creating and writing The Last of Us franchise and its television adaptation.
-
D.
Matt Shafer
Matt Shafer, better known by his stage name Uncle Kracker, is an American singer-songwriter and musician recognized for his blend of rock, country, and pop influences.
-
E.
Joel Veness
Joel Veness is a computer scientist and researcher known for his work in artificial intelligence and algorithmic information theory, including collaborations with Marcus Hutter.
- 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_69ca84dc04488190b9c91193976c0960 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda215b3108190a897552e1dc91cc4 |
completed | April 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c42c9fe081908145911cad6723c2 |
completed | April 5, 2026, 2:08 a.m. |
Created at: March 30, 2026, 8:28 p.m.