Triple
T23955260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NASCAR Weekly Racing Series |
E603769
|
entity |
| Predicate | benefitsForTracks |
P101952
|
FINISHED |
| Object | NASCAR branding |
—
|
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: NASCAR branding | Statement: [NASCAR Weekly Racing Series, benefitsForTracks, NASCAR branding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitsForTracks Context triple: [NASCAR Weekly Racing Series, benefitsForTracks, NASCAR branding]
-
A.
hasTrackFeatures
Indicates that something possesses or is associated with specific track-related characteristics or attributes.
-
B.
benefitCharacteristic
Indicates that one entity possesses a quality or feature that provides an advantage, usefulness, or positive effect to another entity.
-
C.
containsAdditionalTracksBeyond
Indicates that one entity includes more tracks or items than are present in another referenced set or version.
-
D.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
E.
benefitAppliesTo
chosen
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
- 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_69e2954222288190a7323554d0cca8d7 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d0d616ec81908c796894f40f3015 |
completed | April 29, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:21 p.m.