Triple
T37496997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Eyasi |
E931851
|
entity |
| Predicate | hasWetlandAreas |
P24156
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lake Eyasi, hasWetlandAreas, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWetlandAreas Context triple: [Lake Eyasi, hasWetlandAreas, yes]
-
A.
containsWetland
chosen
Indicates that one area or region includes within its boundaries a wetland ecosystem.
-
B.
hasNearbyWetlandRegion
Indicates that a given location or area is situated close to, or in the vicinity of, a wetland region.
-
C.
hasRiparianZone
Indicates that an area is adjacent to and ecologically influenced by a body of water, forming its riparian (riverbank or shoreline) zone.
-
D.
hasWetlandsAtMouth
Indicates that a watercourse or water body has wetlands located at or surrounding its mouth where it meets another body of water.
-
E.
wetlandSystem
Indicates that one entity is a wetland system associated with, containing, or characterizing the other 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:17 p.m.