Triple
T28950391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nisa PDO |
E730995
|
entity |
| Predicate | protectsProduct |
P87853
|
FINISHED |
| Object | Queijo Nisa |
—
|
NE NERFINISHED |
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: Queijo Nisa | Statement: [Nisa PDO, protectsProduct, Queijo Nisa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectsProduct Context triple: [Nisa PDO, protectsProduct, Queijo Nisa]
-
A.
protectsProductType
chosen
Indicates that one entity provides protection or safeguarding specifically for a certain type or category of product.
-
B.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
C.
providesProtectionIn
Indicates that one entity offers protection or safeguarding to another entity within a specified context, location, or situation.
-
D.
providesProtectionAgainst
Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
-
E.
protectionType
Indicates the kind or method of protection that is applied to or associated with an 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 28, 2026, 8:43 a.m.