Triple
T4830212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swanson |
E107925
|
entity |
| Predicate | hasTargetUse |
P57747
|
FINISHED |
| Object | cooking base for soups |
—
|
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: cooking base for soups | Statement: [Swanson, hasTargetUse, cooking base for soups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetUse Context triple: [Swanson, hasTargetUse, cooking base for soups]
-
A.
usesTarget
Indicates that one entity employs, applies, or operates on another entity as its target or object of action.
-
B.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
C.
usesTargetNetwork
Indicates that an entity operates or communicates through a specified target network as its underlying connection or infrastructure.
-
D.
usesTargetingSystem
Indicates that an entity employs or relies on a specific targeting system to aim at or select a target.
-
E.
targetsUseCase
chosen
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.