Triple
T15790696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audi A6 e-tron |
E382855
|
entity |
| Predicate | targetCompetitorSegment |
P1375
|
FINISHED |
| Object | Tesla Model S segment |
—
|
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: Tesla Model S segment | Statement: [Audi A6 e-tron, targetCompetitorSegment, Tesla Model S segment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetCompetitorSegment Context triple: [Audi A6 e-tron, targetCompetitorSegment, Tesla Model S segment]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
attractsCompetitorsFrom
Indicates that one entity draws or lures competitors away from another entity or location.
-
C.
marketSegmentCoverage
Indicates the extent to which a product, service, or campaign reaches or serves the intended market segment(s).
-
D.
competesWith
chosen
Indicates that two entities are in rivalry or opposition, each striving to outperform or gain advantage over the other in the same domain or objective.
-
E.
targetAudienceRank
Indicates the relative priority or importance level assigned to a particular audience segment compared to other potential audiences.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d819c881908bc43a6124a1bb2e |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.