Triple
T18463845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassino Plant |
E451106
|
entity |
| Predicate | hasProductSegment |
P7224
|
FINISHED |
| Object | premium segment vehicles |
—
|
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: premium segment vehicles | Statement: [Cassino Plant, hasProductSegment, premium segment vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProductSegment Context triple: [Cassino Plant, hasProductSegment, premium segment vehicles]
-
A.
hasMarketSegmentFor
Indicates that an entity targets or serves a specific market segment for its products or services.
-
B.
hasUserSegment
Indicates that an entity is associated with a particular user segment or group of users defined by shared characteristics or behaviors.
-
C.
hasRetailSegment
Indicates that an entity is associated with, operates within, or targets a specific retail market segment.
-
D.
hasProduct
Indicates that an entity possesses, offers, or is associated with a particular product.
-
E.
hasMarketingCategory
chosen
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a8190508190a74b1d3482364905 |
completed | April 19, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:33 a.m.