Triple
T8015301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giresun |
E186597
|
entity |
| Predicate | hasHazelnutBrandReputation |
P73564
|
FINISHED |
| Object | high-quality Turkish hazelnuts |
—
|
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: high-quality Turkish hazelnuts | Statement: [Giresun, hasHazelnutBrandReputation, high-quality Turkish hazelnuts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHazelnutBrandReputation Context triple: [Giresun, hasHazelnutBrandReputation, high-quality Turkish hazelnuts]
-
A.
hasBrandReputation
chosen
Indicates that an entity possesses a certain level or type of perceived quality, trustworthiness, or public image associated with its brand.
-
B.
hasBrandRecognitionFor
Indicates that one entity is aware of, recognizes, or can identify the brand of another entity.
-
C.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
D.
hasGlobalBrand
Indicates that an entity possesses a brand that is recognized and operates across multiple countries or worldwide.
-
E.
manufacturerReputation
Indicates the perceived reliability, quality, and trustworthiness associated with a product’s manufacturer.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df24e4c8190ae1c46e97e54787d |
completed | March 31, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:20 p.m.