Triple
T19799917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diyaluma Falls |
E475644
|
entity |
| Predicate | rankingByHeightInSriLanka |
P137373
|
FINISHED |
| Object | second tallest waterfall in Sri Lanka |
—
|
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: second tallest waterfall in Sri Lanka | Statement: [Diyaluma Falls, rankingByHeightInSriLanka, second tallest waterfall in Sri Lanka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingByHeightInSriLanka Context triple: [Diyaluma Falls, rankingByHeightInSriLanka, second tallest waterfall in Sri Lanka]
-
A.
countryRankByHeight
Indicates the relative position of a country when countries are ordered by the height of something (e.g., average elevation, tallest point, or average citizen height).
-
B.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
C.
rankingByHeightInZimbabwe
Indicates an ordering of entities based on their height specifically within the context or population of Zimbabwe.
-
D.
rankByHeightPakistan
Indicates an ordering of entities based on their height specifically within the context of Pakistan.
-
E.
rankingByHeightInJapan
Indicates the relative order of entities based on their height specifically within the context of Japan.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653cb865c81909696d2b37476f62f |
completed | April 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:49 p.m.