Triple
T11385708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother's Day |
E269709
|
entity |
| Predicate | hasCommercialAspects |
P74963
|
FINISHED |
| Object | greeting card sales |
—
|
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: greeting card sales | Statement: [Mother's Day, hasCommercialAspects, greeting card sales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialAspects Context triple: [Mother's Day, hasCommercialAspects, greeting card sales]
-
A.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
B.
hasCommercialImportance
chosen
Indicates that something possesses economic or business value significant enough to impact trade, revenue, or market activity.
-
C.
hasCommercialAxis
Indicates that there exists a primary direction, route, or area along which commercial or business activities are concentrated or organized.
-
D.
commercialSignificance
Indicates that something has notable economic or business importance, value, or impact in a commercial context.
-
E.
isNonCommercial
Indicates that the associated entity, use, or activity is not intended for or involved in commercial, profit-generating purposes.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.