Triple
T36073248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leavine Family Racing |
E1043422
|
entity |
| Predicate | ranFullTime |
P184550
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Leavine Family Racing, ranFullTime, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ranFullTime Context triple: [Leavine Family Racing, ranFullTime, 2016]
-
A.
runsMostly
Indicates that an entity performs running as its primary or most frequent activity compared to other activities.
-
B.
completedFullTerm
Indicates that an entity has finished the entire expected duration or course of a specified process, period, or term without interruption or early termination.
-
C.
ranForOfficeIn
Indicates that a person was a candidate seeking election to a particular office in a specified political contest or time period.
-
D.
ranOn
Indicates that an entity executed or operated on a particular platform, system, or environment.
-
E.
ranAgainst
Indicates that one entity competed as an opponent to another in an election or similar contest.
- F. None of above. chosen
Provenance (4 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_69f76e2fd3248190b900d9a492bf5a7a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b35e32d481909ef0220e6f6ff4a8 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2c66054819083897e25edb65ba7 |
completed | May 3, 2026, 8:40 p.m. |
Created at: May 3, 2026, 4:08 p.m.