Triple
T5193429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furious 7 |
E117210
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Tej Parker |
E248788
|
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: Tej Parker | Statement: [Furious 7, featuresCharacter, Tej Parker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tej Parker Context triple: [Furious 7, featuresCharacter, Tej Parker]
-
A.
Tej Parker
chosen
Tej Parker is a tech-savvy mechanic and hacker in the Fast & Furious film franchise, known for his intelligence, humor, and close partnership with Roman Pearce.
-
B.
Kim Parker
Kim Parker is a comedic, outspoken teenage character from the sitcom "Moesha," later becoming a central figure in its spin-off series "The Parkers."
-
C.
Joy Parker
Joy Parker was the wife of acclaimed English actor Paul Scofield, with whom she shared a long marriage and family life.
-
D.
Carol Parker
Carol Parker is best known as the wife of Marlon Jackson, a member of the famed Jackson family and former singer of The Jackson 5.
-
E.
Jolene Parker
Jolene Parker is a fictional character portrayed by actress Rachel Brosnahan.
- 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_69bd4462ed04819084fcb01eb9d2fa74 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79f142488190bc6c57b8ff7ef894 |
completed | March 20, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beefbcbd1881908afc477150135961 |
completed | March 21, 2026, 7:21 p.m. |
Created at: March 20, 2026, 1:46 p.m.