Triple
T13541571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan de Bont |
E323397
|
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: [Jan de Bont, notableWork, Speed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Speed Context triple: [Jan de Bont, 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 is a small town located in Edgecombe County, North Carolina, United States.
-
C.
Speed
"Speed" is a film featuring Indian actor Sanjay Suri in a prominent role.
-
D.
Speed
Speed is a witty, pun-loving servant and comic figure in Shakespeare’s play "The Two Gentlemen of Verona."
-
E.
Speed
Speed is a Marvel Comics superhero and member of the Young Avengers known for his superhuman velocity and resemblance to Quicksilver.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd8ba10819098faadcc6adf251e |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d9eaff881909a3cd9e88bb4ec5e |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.