Triple
T5138609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pistor |
E115889
|
entity |
| Predicate | relatedToProduct |
P62838
|
FINISHED |
| Object | bread |
—
|
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: bread | Statement: [Pistor, relatedToProduct, bread]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToProduct Context triple: [Pistor, relatedToProduct, bread]
-
A.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
relatedToProject
Indicates that an entity has a connection or association with a specific project, without specifying the exact nature of that involvement.
-
C.
relatedBenefit
Indicates that one entity provides an advantage, gain, or positive outcome that is connected or attributable to another entity.
-
D.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
E.
relatedBrand
Indicates a relationship where one brand is associated with, connected to, or otherwise related to another brand.
- F. None of above. chosen
Provenance (4 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7fee42748190967013828973cce0 |
completed | March 20, 2026, 5:12 p.m. |
Created at: March 20, 2026, 1:43 p.m.