Triple
T11421270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diguillín River |
E270624
|
entity |
| Predicate | hasNearbyHumanActivity |
P93890
|
FINISHED |
| Object | crop cultivation |
—
|
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: crop cultivation | Statement: [Diguillín River, hasNearbyHumanActivity, crop cultivation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyHumanActivity Context triple: [Diguillín River, hasNearbyHumanActivity, crop cultivation]
-
A.
nearbyActivity
Indicates that an activity occurs close in space or proximity to a specified entity or location.
-
B.
hasOpenSpaceNearby
Indicates that an entity is located near or adjacent to an area that is open, unobstructed, or undeveloped.
-
C.
hasNotableNearbyEntity
Indicates that one entity has another significant or noteworthy entity located in its close physical or contextual proximity.
-
D.
hasNearbyEvent
Indicates that an event occurs close in space or time to the referenced entity.
-
E.
hasNearbyAgriculturalActivity
chosen
Indicates that an entity is located close enough to agricultural operations or land use for those activities to be considered relevant or influential to it.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801b20ce08190befc98379b879985 |
completed | April 9, 2026, 7:44 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.