Triple
T17077321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia Café au Lait |
E414382
|
entity |
| Predicate | isPartOfMarketSegment |
P116570
|
FINISHED |
| Object | Japanese ready-to-drink coffee 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: Japanese ready-to-drink coffee market | Statement: [Georgia Café au Lait, isPartOfMarketSegment, Japanese ready-to-drink coffee market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfMarketSegment Context triple: [Georgia Café au Lait, isPartOfMarketSegment, Japanese ready-to-drink coffee market]
-
A.
hasMarketSegmentFor
Indicates that an entity targets or serves a specific market segment for its products or services.
-
B.
governsMarketSegment
Indicates that an entity has controlling influence or regulatory authority over a particular market segment.
-
C.
hasMarketSector
chosen
Indicates that an entity operates within, is associated with, or belongs to a particular market sector or industry segment.
-
D.
majorSegmentOf
Indicates that one entity constitutes a principal or most significant part of another larger whole.
-
E.
brandSegment
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc625c48190b679a521180e10ad |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.