Triple
T5708803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Motor Speedway |
E125852
|
entity |
| Predicate | frontstretchLength |
P30560
|
FINISHED |
| Object | 1980 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: 1980 feet | Statement: [Charlotte Motor Speedway, frontstretchLength, 1980 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontstretchLength Context triple: [Charlotte Motor Speedway, frontstretchLength, 1980 feet]
-
A.
frontLength
Indicates the length measurement of the front side or edge of an object relative to its overall dimensions.
-
B.
frontLineLength
Indicates the total measured extent of the front line where opposing forces or boundaries directly face each other.
-
C.
trailLengthApprox
Indicates an approximate measurement of the total length of a trail.
-
D.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
E.
mainStraightLengthM
chosen
Indicates the length, measured in meters, of the main straight segment (typically of a track, road, or similar linear feature).
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248ab6a88190be17bdc32c36e5cb |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:46 p.m.