Triple
T12045676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto Club Speedway |
E286780
|
entity |
| Predicate | frontStretchLength |
P102933
|
FINISHED |
| Object | 3100 feet |
—
|
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: 3100 feet | Statement: [Auto Club Speedway, frontStretchLength, 3100 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontStretchLength Context triple: [Auto Club Speedway, frontStretchLength, 3100 feet]
-
A.
frontLength
Indicates the length measurement of the front side or edge of an object relative to its overall dimensions.
-
B.
frontHornLength
Indicates the length measurement of an entity’s front horn in a specified unit.
-
C.
extensionLength
Indicates the length or magnitude of an extension from a reference point or base object.
-
D.
hasLongStretchIn
Indicates that something extends for a considerable or continuous distance within a specified area, medium, or context.
-
E.
frontLineLength
Indicates the total measured extent of the front line where opposing forces or boundaries directly face each other.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:47 p.m.