Triple
T6244476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casella Family Brands |
E139683
|
entity |
| Predicate | hasTargetSegment |
P14889
|
FINISHED |
| Object | mass-market wine consumers |
—
|
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: mass-market wine consumers | Statement: [Casella Family Brands, hasTargetSegment, mass-market wine consumers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetSegment Context triple: [Casella Family Brands, hasTargetSegment, mass-market wine consumers]
-
A.
hasTarget
chosen
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
B.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
C.
hasExpressSegments
Indicates that a route, service, or path includes segments that are designated as express, skipping certain intermediate stops or steps.
-
D.
hasSegmentType
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
E.
usesTargetingSystem
Indicates that an entity employs or relies on a specific targeting system to aim at or select a target.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631c63d48190a41ec1232aecb373 |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:23 p.m.