Triple
T17582405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lurigancho-Chosica District |
E428235
|
entity |
| Predicate | hasRuralType |
P85002
|
FINISHED |
| Object | valley agricultural zones |
—
|
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: valley agricultural zones | Statement: [Lurigancho-Chosica District, hasRuralType, valley agricultural zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralType Context triple: [Lurigancho-Chosica District, hasRuralType, valley agricultural zones]
-
A.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
B.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
C.
hasRuralLandscapeType
chosen
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
D.
hasRuralLocality
Indicates that an entity possesses, includes, or is associated with a rural locality (such as a village, hamlet, or countryside settlement) within its scope or jurisdiction.
-
E.
isInRuralAreaOf
Indicates that one entity is located within the rural area or countryside region associated with another 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cf556881908d2935b3761f65df |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.