Triple
T24816401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa María del Oro Lake |
E620932
|
entity |
| Predicate | hasShoreDevelopmentLevel |
P44587
|
FINISHED |
| Object | moderate tourism infrastructure |
—
|
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: moderate tourism infrastructure | Statement: [Santa María del Oro Lake, hasShoreDevelopmentLevel, moderate tourism infrastructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoreDevelopmentLevel Context triple: [Santa María del Oro Lake, hasShoreDevelopmentLevel, moderate tourism infrastructure]
-
A.
shorelineDevelopment
chosen
Indicates the extent to which human-made structures or modifications have been built along a shoreline.
-
B.
hasShoreFeature
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
C.
hasWaterfrontDevelopment
Indicates that a location or property includes or is associated with constructed developments directly along or adjacent to a body of water.
-
D.
hasShorelineUse
Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
-
E.
hasShoreOn
Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:02 a.m.