Triple
T35617760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam Stevens |
E1029220
|
entity |
| Predicate | hasWorkedWithDriver |
P103677
|
FINISHED |
| Object | Kyle Busch |
—
|
NE NERFINISHED |
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: Kyle Busch | Statement: [Adam Stevens, hasWorkedWithDriver, Kyle Busch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkedWithDriver Context triple: [Adam Stevens, hasWorkedWithDriver, Kyle Busch]
-
A.
hasFormerDriver
Indicates that an entity previously served as a driver for another entity but no longer holds that role.
-
B.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
C.
alsoAssociatedWithDriver
Indicates that an entity has an additional or secondary association with a specified driver, beyond any primary or previously stated driver relationship.
-
D.
associatedWithDriver
chosen
Indicates that one entity has a connection or relationship with a specific driver, such as being linked, assigned, or otherwise related to that driver.
-
E.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
- F. None of above.
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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 3, 2026, 4:05 p.m.