Triple
T4326298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python (via Snowpark) |
E96640
|
entity |
| Predicate | targetsUsers |
P10541
|
FINISHED |
| Object | data engineers |
—
|
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: data engineers | Statement: [Python (via Snowpark), targetsUsers, data engineers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsUsers Context triple: [Python (via Snowpark), targetsUsers, data engineers]
-
A.
targetsGroup
chosen
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
B.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
C.
targetOwner
Indicates that one entity is the owner or primary possessor of a specified target entity.
-
D.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
E.
traditionalUsers
Indicates that the associated users adhere to long-established or customary practices, methods, or preferences in the given context.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3513020f481909ff2fec3934f3002 |
completed | March 12, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:13 p.m.