Triple
T12073847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lentille verte du Puy |
E287493
|
entity |
| Predicate | legalProtectionScope |
P103066
|
FINISHED |
| Object | geographical origin |
—
|
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: geographical origin | Statement: [Lentille verte du Puy, legalProtectionScope, geographical origin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalProtectionScope Context triple: [Lentille verte du Puy, legalProtectionScope, geographical origin]
-
A.
legalScope
Indicates the range, boundaries, or extent of authority, applicability, or effect that something has under a particular legal framework or rule.
-
B.
legalProtectionFor
Indicates that one entity provides or is subject to legal safeguards, rights, or defenses in favor of another entity or interest.
-
C.
legalCodeAppliesTo
Indicates that a particular legal code or statute is applicable to, or governs, a specified subject, situation, or entity.
-
D.
legalTopicCoverage
Indicates that one entity (such as a document, service, or resource) addresses, discusses, or is relevant to a particular legal topic or area of law.
-
E.
legalSetting
Indicates that an entity is involved in, occurs within, or is characterized by a formal legal context, such as courts, legal procedures, or judicial environments.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:48 p.m.