Triple
T17413844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bismarck Sea watershed |
E423436
|
entity |
| Predicate | hasRiverMouthsAlong |
P57845
|
FINISHED |
| Object | north coast of Papua New Guinea |
—
|
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: north coast of Papua New Guinea | Statement: [Bismarck Sea watershed, hasRiverMouthsAlong, north coast of Papua New Guinea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverMouthsAlong Context triple: [Bismarck Sea watershed, hasRiverMouthsAlong, north coast of Papua New Guinea]
-
A.
riverMouthCountry
Indicates the country in which a river’s mouth (where it flows into another body of water) is located.
-
B.
hasWetlandsAtMouth
Indicates that a watercourse or water body has wetlands located at or surrounding its mouth where it meets another body of water.
-
C.
riverMouthAt
Indicates that the mouth or endpoint of a river is located at a specified place or geographic feature.
-
D.
hasHumanSettlementAtMouth
Indicates that a human settlement is located at the mouth (outflow point) of a geographic feature such as a river or valley.
-
E.
riverMouthRegion
chosen
Indicates the region or area where a river flows into a larger body of water, such as a sea, lake, or another river.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44230fc688190a6a7edc12d9e9947 |
completed | April 19, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.