Triple
T6391187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Daniels |
E143829
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Speed |
E238638
|
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: Speed | Statement: [Jeff Daniels, notableWork, Speed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Speed Context triple: [Jeff Daniels, notableWork, Speed]
-
A.
Speed
chosen
Speed is a 1994 action thriller film starring Keanu Reeves and Sandra Bullock, centered on a city bus that will explode if its speed drops below 50 miles per hour.
-
B.
SPEED
SPEED was an American cable and satellite television network focused on motorsports and automotive programming.
-
C.
Speed Law
"Speed Law" is a track from Mos Def's acclaimed hip-hop album *Black on Both Sides*, known for its energetic delivery and socially conscious lyricism.
-
D.
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.
-
E.
Pace
Pace is a popular American brand best known for its chunky salsas and Mexican-style sauces.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0687c7fdc819099cbbb937dec215e |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6388b02888190989623c658469a5a |
completed | March 27, 2026, 7:58 a.m. |
Created at: March 22, 2026, 4:34 p.m.