Triple
T16318055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darrell Waltrip |
E396221
|
entity |
| Predicate | beganCupSeriesCareer |
P103671
|
FINISHED |
| Object | 1972 |
—
|
LITERAL 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: 1972 | Statement: [Darrell Waltrip, beganCupSeriesCareer, 1972]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beganCupSeriesCareer Context triple: [Darrell Waltrip, beganCupSeriesCareer, 1972]
-
A.
beganAmateurCareer
Indicates that an entity started its amateur-level career or involvement in a particular field or activity.
-
B.
beganBroadcastingCareer
Indicates that an entity started or initiated its professional career in broadcasting at a particular time or context.
-
C.
numberOfCupSeriesChampionships
Indicates the total count of Cup Series championships that an entity has won.
-
D.
beganInLeagueSeason
Indicates that an entity (such as a team, player, or competition) began its participation or activity during a specified league season.
-
E.
cupSeriesDebutSeason
chosen
Indicates the season in which an entity first participated in a Cup series competition.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b3e3e081908a996b3e57ca4e32 |
completed | April 17, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69e219fc72c881909d452274e7af8238 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.