Triple
T13520073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Code 46 |
E322869
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Tim Robbins |
E56260
|
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: Tim Robbins | Statement: [Code 46, starring, Tim Robbins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim Robbins Context triple: [Code 46, starring, Tim Robbins]
-
A.
Tim Robbins
chosen
Tim Robbins is an American actor, director, and producer best known for his roles in films such as The Shawshank Redemption, Mystic River, and Bull Durham.
-
B.
William Hurt
William Hurt was an acclaimed American actor known for his intense, introspective performances in films such as "Kiss of the Spider Woman," "Broadcast News," and "The Big Chill."
-
C.
James Woods
James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
-
D.
Peter Strauss
Peter Strauss is an American actor best known for his work in television miniseries and films, including prominent roles in dramas throughout the 1970s and 1980s.
-
E.
Jeff Bridges
Jeff Bridges is an acclaimed American actor known for his versatile performances in films such as "The Big Lebowski," "Crazy Heart," and "True Grit."
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa3df0c8190804174695587f0ea |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75498153c819096a28a7f0b608ff5 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:44 p.m.