Triple
T14080193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius Tennon |
E338844
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Faster |
E582871
|
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: Faster | Statement: [Julius Tennon, notableWork, Faster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faster Context triple: [Julius Tennon, notableWork, Faster]
-
A.
Faster
chosen
Faster is a 2010 American action thriller film starring Dwayne Johnson as an ex-con seeking revenge after his brother’s murder.
-
B.
Faster
"Faster" is a track from the Girls Aloud album "On Your Radar," showcasing the group's upbeat pop-dance sound.
-
C.
Quick Fast
"Quick Fast" is a hip-hop track by the California rap duo Audio Push, known for its energetic delivery and West Coast-influenced production.
-
D.
Fast as You
"Fast as You" is a popular country song by American singer-songwriter Dwight Yoakam, known for its upbeat honky-tonk style and enduring radio appeal.
-
E.
Speedy
Speedy is a 1928 silent comedy film starring Harold Lloyd, known for its energetic New York City setting and memorable Coney Island and baseball sequences.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5f759c81909bfd60ab35b0937b |
completed | April 14, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb672c08081908e1ff9030745776a |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:21 p.m.