Triple
T1359589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indianapolis Motor Speedway |
E29067
|
entity |
| Predicate | turns |
P28004
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Indianapolis Motor Speedway, turns, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turns Context triple: [Indianapolis Motor Speedway, turns, 4]
-
A.
turningPointIn
Indicates that an event or situation serves as a decisive change or pivotal moment within a larger process, narrative, or development.
-
B.
rotatesAmong
Indicates that an entity takes turns occupying or performing a role, position, or function in sequence with other entities.
-
C.
turnedPro
Indicates that an individual transitioned from amateur status to professional status in a particular field or activity.
-
D.
lays
Indicates that one entity deposits or places something, typically eggs or objects, onto a surface or in a location.
-
E.
catches
Indicates that one entity successfully seizes, intercepts, or takes hold of another entity, often stopping its motion or preventing its escape.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c290db288190910fcfa17e902663 |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef7700c819099b294e8d9320e70 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c20fd1fc8190977a768b1ed2d23b |
completed | March 1, 2026, 10:47 p.m. |
Created at: March 1, 2026, 7:56 p.m.