Triple
T23350771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brewster & Co. |
E592000
|
entity |
| Predicate | servedMarketSegment |
P120776
|
FINISHED |
| Object | luxury automobile market |
—
|
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: luxury automobile market | Statement: [Brewster & Co., servedMarketSegment, luxury automobile market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedMarketSegment Context triple: [Brewster & Co., servedMarketSegment, luxury automobile market]
-
A.
marketSegmentType
Indicates the specific category or segment of the market that an entity, product, or service is targeted toward or associated with.
-
B.
governsMarketSegment
Indicates that an entity has controlling influence or regulatory authority over a particular market segment.
-
C.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
D.
hasMarketSegmentFor
chosen
Indicates that an entity targets or serves a specific market segment for its products or services.
-
E.
marketSegmentCoverage
Indicates the extent to which a product, service, or campaign reaches or serves the intended market segment(s).
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a1401748190b77df0a45c2aeebf |
completed | April 29, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:19 p.m.