Triple
T15792442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Huallaga Valley |
E382891
|
entity |
| Predicate | hasLegalCrop |
P120036
|
FINISHED |
| Object | coffee |
—
|
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: coffee | Statement: [Upper Huallaga Valley, hasLegalCrop, coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalCrop Context triple: [Upper Huallaga Valley, hasLegalCrop, coffee]
-
A.
hasLegalRight
Indicates that an entity possesses an officially recognized legal entitlement or permission to perform an action or hold a claim regarding another entity.
-
B.
hasLegalOrientation
Indicates that an entity possesses a particular legal stance, status, or alignment within a legal framework.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
hasLegalVenue
Indicates that a legal case, dispute, or action is appropriately and lawfully brought before a particular court or jurisdiction.
-
E.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d9623081908496cdfdf86a078a |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e006b17f7881908b8c7a37f0af4581 |
completed | April 15, 2026, 9:44 p.m. |
Created at: April 10, 2026, 4:48 a.m.