Triple
T33603153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yahuarcocha Lake |
E860774
|
entity |
| Predicate | hasShoreNear |
P181693
|
FINISHED |
| Object | urban area of Ibarra |
—
|
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: urban area of Ibarra | Statement: [Yahuarcocha Lake, hasShoreNear, urban area of Ibarra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoreNear Context triple: [Yahuarcocha Lake, hasShoreNear, urban area of Ibarra]
-
A.
hasShoreOn
Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
-
B.
hasShoreFeature
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
C.
hasNearbyCoast
Indicates that one location is situated close to a coastline or seashore.
-
D.
shoreHas
Indicates that a shore possesses, contains, or is characterized by a particular feature, object, or attribute.
-
E.
hasPrimaryLanguageOfNearbyShore
Indicates that an entity uses as its primary language the language predominantly spoken along the nearby shore or coastal area.
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f7805c25dc8190b9977c561ba15975 |
completed | May 3, 2026, 5:05 p.m. |
Created at: May 1, 2026, 1:41 a.m.