Triple
T9825282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speed |
E238638
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Joe Morton |
E206260
|
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: Joe Morton | Statement: [Speed, starring, Joe Morton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Morton Context triple: [Speed, starring, Joe Morton]
-
A.
Joe Morton
chosen
Joe Morton is an American actor known for his versatile film and television roles, including notable performances in projects like "Terminator 2: Judgment Day" and the TV series "Scandal."
-
B.
Gary Cole
Gary Cole is an American actor known for his versatile roles in film and television, including memorable performances in "Office Space," "The Brady Bunch Movie," and numerous acclaimed TV series.
-
C.
Gerald McRaney
Gerald McRaney is an American actor best known for his television roles in series such as "Simon & Simon," "Major Dad," and "This Is Us."
-
D.
Leo Willis
Leo Willis was an American character actor active during the silent and early sound film eras, often appearing in comedies alongside stars like Harold Lloyd.
-
E.
Joel Murray
Joel Murray is an American actor and comedian known for his character roles in film and television, as well as for his voice work in animated projects.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3181c688190afea3b27ee392a30 |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20d2cb5108190aa15b60ea76bfa78 |
completed | April 5, 2026, 7:20 a.m. |
Created at: March 30, 2026, 8:31 p.m.