Triple
T19044794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Balkhash |
E466102
|
entity |
| Predicate | rankByAreaInKazakhstan |
P134866
|
FINISHED |
| Object | second-largest lake in Kazakhstan |
—
|
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-largest lake in Kazakhstan | Statement: [Lake Balkhash, rankByAreaInKazakhstan, second-largest lake in Kazakhstan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInKazakhstan Context triple: [Lake Balkhash, rankByAreaInKazakhstan, second-largest lake in Kazakhstan]
-
A.
rankInRussiaByArea
Indicates the position of an entity in an ordered list of entities in Russia sorted by their area size.
-
B.
distanceFromAlmaty_km
Indicates the distance, measured in kilometers, between a given place or object and the city of Almaty.
-
C.
rankInChinaByArea
Indicates the position of an entity in an ordered list of entities in China when sorted by their area size.
-
D.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
E.
areaTotalSquareKilometers
Indicates the total size of something measured in square kilometers.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d803b2b08190b057d4b5bc555d4f |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
| PDg | Predicate description generation | batch_69e4c0fc3c4c8190abbfe06e1bd3325c |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 12:03 p.m.